National Library of Energy BETA

Sample records for gross household income

  1. Loan Programs for Low- and Moderate-Income Households | Department...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Programs for Low- and Moderate-Income Households Loan Programs for Low- and Moderate-Income Households Better Buildings Residential Network Multifamily and Low-Income Housing Peer ...

  2. Fact #565: April 6, 2009 Household Gasoline Expenditures by Income |

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Department of Energy 5: April 6, 2009 Household Gasoline Expenditures by Income Fact #565: April 6, 2009 Household Gasoline Expenditures by Income In the annual Consumer Expenditure Survey, household incomes are grouped into five equal parts called quintiles (each quintile is 20%). Households in the second and third quintiles consistently have a higher share of spending on gasoline each year than households in the other quintiles. Household Gasoline Expenditures by Income Quintile Bar graph

  3. Delivering Energy Efficiency to Middle Income Single Family Households

    SciTech Connect (OSTI)

    none,

    2011-12-01

    Provides state and local policymakers with information on successful approaches to the design and implementation of residential efficiency programs for households ineligible for low-income programs.

  4. "Table HC7.5 Space Heating Usage Indicators by Household Income...

    U.S. Energy Information Administration (EIA) Indexed Site

    ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ... for 2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ...

  5. Table HC1-3a. Housing Unit Characteristics by Household Income...

    Gasoline and Diesel Fuel Update (EIA)

    RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ... RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ...

  6. Loan Programs for Low- and Moderate-Income Households | Department of

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Energy Programs for Low- and Moderate-Income Households Loan Programs for Low- and Moderate-Income Households Better Buildings Residential Network Multifamily and Low-Income Housing Peer Exchange Call Series: Loan Programs for Low- and Moderate-Income Households, March 13, 2014. Call Slides and Discussion Summary (919.64 KB) More Documents & Publications EcoHouse Program Overview Strengthening Relationships Between Energy Programs and Housing Programs Targeted Marketing and Program

  7. Effect of Income on Appliances in U.S. Households, The

    Reports and Publications (EIA)

    2004-01-01

    Entails how people live, the factors that cause the most differences in home lifestyle, including energy use in geographic location, socioeconomics and household income.

  8. Forum on Enhancing the Delivery of Energy Efficiency to Middle Income Households: Discussion Summary

    SciTech Connect (OSTI)

    none,

    2012-09-20

    Summarizes discussions and recommendations from a forum for practitioners and policymakers aiming to strengthen residential energy efficiency program design and delivery for middle income households.

  9. EPA Webinar: Bringing Energy Efficiency and Renewable Housing to Low-Income Households

    Broader source: Energy.gov [DOE]

    Hosted by the U.S. Environmental Protection Agency, this webinar will explore the topic of linking and leveraging energy efficiency and renewable energy programs for limited-income households, including the need to coordinate with other energy assistance programs.

  10. Better Buildings Residential Network Multi-Family & Low-Income Housing Peer Exchange Call Series: Loan Programs for Low- and Moderate-Income Households, March 13, 2014

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Family & Low-Income Housing Peer Exchange Call Series: Loan Programs for Low- and Moderate-Income Households March 13, 2014 Agenda  Call Logistics and Introductions  Featured Participants  Becca Harmon Murphy (Indianapolis Neighborhood Housing Partnership)  Discussion:  What strategies or approaches has your program used to build interest in your loan programs for moderate- and low-income households? What has worked well, and why do you think it was effective?  What

  11. The Impact of Carbon Control on Low-Income Household Electricity and Gasoline Expenditures

    SciTech Connect (OSTI)

    Eisenberg, Joel Fred

    2008-06-01

    In July of 2007 The Department of Energy's (DOE's) Energy Information Administration (EIA) released its impact analysis of 'The Climate Stewardship And Innovation Act of 2007,' known as S.280. This legislation, cosponsored by Senators Joseph Lieberman and John McCain, was designed to significantly cut U.S. greenhouse gas emissions over time through a 'cap-and-trade' system, briefly described below, that would gradually but extensively reduce such emissions over many decades. S.280 is one of several proposals that have emerged in recent years to come to grips with the nation's role in causing human-induced global climate change. EIA produced an analysis of this proposal using the National Energy Modeling System (NEMS) to generate price projections for electricity and gasoline under the proposed cap-and-trade system. Oak Ridge National Laboratory integrated those price projections into a data base derived from the EIA Residential Energy Consumption Survey (RECS) for 2001 and the EIA public use files from the National Household Transportation Survey (NHTS) for 2001 to develop a preliminary assessment of impact of these types of policies on low-income consumers. ORNL will analyze the impacts of other specific proposals as EIA makes its projections for them available. The EIA price projections for electricity and gasoline under the S.280 climate change proposal, integrated with RECS and NHTS for 2001, help identify the potential effects on household electric bills and gasoline expenditures, which represent S.280's two largest direct impacts on low-income household budgets in the proposed legislation. The analysis may prove useful in understanding the needs and remedies for the distributive impacts of such policies and how these may vary based on patterns of location, housing and vehicle stock, and energy usage.

  12. Weatherization assistance for low-income households: An evaluation of local program performance

    SciTech Connect (OSTI)

    Schweitzer, M.; Rayner, S.; Wolfe, A.K.; Mason, T.W.; Ragins, B.R.; Cartor, R.A.

    1987-08-01

    The US Department of Energy's Weatherization Assistance Program (WAP) funds local agencies to provide weatherization services to low-income households. This report describes the most salient features of this program, examines relationships between organization and program outcomes, and presents recommendations for the program's further development. Data were collected by written surveys administered to local weatherization agencies, a telephone survey of 38 states and eight DOE support offices, and site visits to selected local agencies. Locally controlled factors found to be significantly related to program performance include the amount of the weatherization director's time spent on program administration, the use of established client selection criteria, the frequency of evaluation of local goal attainment, and the type of weatherization crews used. Factors controlled at the state or federal levels that influence program performance include delays in state reimbursements of local agency expenditures and local flexibility in the choice of weatherization measures. Data-gathering difficulties experienced during this project indicate a need for possible improvements in goal-setting and record-keeping procedures.

  13. " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1"

    U.S. Energy Information Administration (EIA) Indexed Site

    6 Air Conditioning Characteristics by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Air Conditioning Characteristics"

  14. " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1"

    U.S. Energy Information Administration (EIA) Indexed Site

    HC7.9 Home Appliances Characteristics by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Home Appliances Characteristics" "Total

  15. " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1"

    U.S. Energy Information Administration (EIA) Indexed Site

    3 Lighting Usage Indicators by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Lighting Usage Indicators" "Total U.S. Housing

  16. BENTON PUD LOW INCOME CONSERVATION PROGRAM

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    result in a preference being given to households with incomes below 125% of Federal Poverty Guidelines (FPG) Upper low income households with incomes between 125 and 200%...

  17. housingunit_household2001.pdf

    Annual Energy Outlook [U.S. Energy Information Administration (EIA)]

    ... RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ... RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ...

  18. appl_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ... RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ...

  19. ac_household2001.pdf

    Gasoline and Diesel Fuel Update (EIA)

    RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ... RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ...

  20. spaceheat_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ... RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ...

  1. char_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ... Income Relative to Poverty Line Below 100 Percent ...... 15.0 13.2 1.8 Q ...

  2. "Table HC7.12 Home Electronics Usage Indicators by Household...

    U.S. Energy Information Administration (EIA) Indexed Site

    ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ... for 2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ...

  3. "Table HC7.10 Home Appliances Usage Indicators by Household...

    U.S. Energy Information Administration (EIA) Indexed Site

    ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ... for 2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ...

  4. appl_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    Appliances Tables (Million U.S. Households; 60 pages, 240 kb) Contents Pages HC5-1a. Appliances by Climate Zone, Million U.S. Households, 2001 5 HC5-2a. Appliances by Year of Construction, Million U.S. Households, 2001 5 HC5-3a. Appliances by Household Income, Million U.S. Households, 2001 5 HC5-4a. Appliances by Type of Housing Unit, Million U.S. Households, 2001 5 HC5-5a. Appliances by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 5 HC5-6a. Appliances by Type of Rented

  5. Samantha Gross

    Broader source: Energy.gov [DOE]

    Samantha Gross is the Director for International Climate and Clean Energy at the Office of International Affairs in the U.S. Department of Energy. She directs U.S. activities under the Clean Energy...

  6. Targeted Marketing and Program Design for Low- and Moderate-Income...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Targeted Marketing and Program Design for Low- and Moderate-Income Households Targeted Marketing and Program Design for Low- and Moderate-Income Households Better Buildings ...

  7. homeoffice_household2001.pdf

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    ... RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ... 29.1 5.3 22.7 3.8 1 Below 150 percent of poverty line or 60 percent of median State ...

  8. homeoffice_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ... 29.1 5.3 22.7 3.8 1 Below 150 percent of poverty line or 60 percent of median State income

  9. " Million U.S. Housing Units" ,,"2005 Household...

    U.S. Energy Information Administration (EIA) Indexed Site

    8 Water Heating Characteristics by Household Income, 2005" " Million U.S. Housing Units" ... to 79,999","80,000 or More" "Water Heating Characteristics" ...

  10. What is Gross Up?

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    the payment if we had not paid you the additional amount. For example: If the Relocation reimbursement request submitted 5668. Without a gross up the net payment received ...

  11. Targeted Marketing and Program Design for Low- and Moderate-Income

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Households | Department of Energy Targeted Marketing and Program Design for Low- and Moderate-Income Households Targeted Marketing and Program Design for Low- and Moderate-Income Households Better Buildings Neighborhood Program Low- / Moderate-Income Peer Exchange Call: Targeted Marketing and Program Design for Low- and Moderate-Income Households, Call Slides and Discussion Summary, October 11, 2011. Call Slides and Discussion Summary (615.55 KB) More Documents & Publications Loan

  12. grossWCI.dvi

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Nuclear multifragmentation, Its relation to general physics A rich test-ground of the fundamentals of statistical mechanics. D.H.E. Gross 1 Hahn-Meitner Institute Glienickerstr. 100 14109 Berlin, Germany gross@hmi.de; http://www.hmi.de/people/gross/ 2 Freie Universit¨ at Berlin, Fachbereich Physik. Received: date / Revised version: date Abstract. Heat can flow from cold to hot at any phase separation, even in macroscopic systems. Therefore also Lynden-Bell's famous gravo-thermal catastrophe [1]

  13. Household magnets

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Household magnets Chances are very good that you have experimented with magnets. People have been fascinated with magnetism for thousands of years. As familiar to us as they may be, magnets still have some surprises for us. Here is a small collection of some of our favorite magnet experiments. What happens when we break a magnet in half? Radio Shack sells cheap ceramic magnets in several shapes. Get a ring shaped magnet and break it with pliers or a tap with a hammer. Try to put it back

  14. EIA - Household Transportation report: Household Vehicles Energy...

    U.S. Energy Information Administration (EIA) Indexed Site

    logo printer-friendly version logo for Portable Document Format file Household Vehicles Energy Consumption 1994 August 1997 Release Next Update: EIA has discontinued this series....

  15. Buildings Energy Data Book: 2.9 Low-Income Housing

    Buildings Energy Data Book [EERE]

    Program Definitions DOE Weatherization: Department of Energy's Weatherization Assistance Program DOE Weatherization Eligible Households: Households with incomes at or below 125% of the Federal poverty level, which varies by family size; however, a State may instead elect to use the LIHEAP income standard if its State LIHEAP income standard is at least 125% of the Federal poverty level. Data listed in this chapter include previously weatherized units. DOE Weatherization Eligible Households are a

  16. BC Hydro Brings Energy Savings to Low-Income Families in Canada...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    BC Hydro Brings Energy Savings to Low-Income Families in Canada BC Hydro Brings Energy Savings to Low-Income Families in Canada The number of British Columbia, Canada, households ...

  17. ,"Alaska Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    "Back to Contents","Data 1: Alaska Natural Gas Gross Withdrawals and Production" ... "Date","Alaska Natural Gas Gross Withdrawals (MMcf)","Alaska Natural ...

  18. ,"New York Natural Gas Gross Withdrawals (MMcf)"

    U.S. Energy Information Administration (EIA) Indexed Site

    ...2016 10:10:10 AM" "Back to Contents","Data 1: New York Natural Gas Gross Withdrawals (MMcf)" "Sourcekey","N9010NY2" "Date","New York Natural Gas Gross Withdrawals (MMcf)" ...

  19. ,"New Mexico Natural Gas Gross Withdrawals (MMcf)"

    U.S. Energy Information Administration (EIA) Indexed Site

    ...2016 10:10:09 AM" "Back to Contents","Data 1: New Mexico Natural Gas Gross Withdrawals (MMcf)" "Sourcekey","N9010NM2" "Date","New Mexico Natural Gas Gross Withdrawals (MMcf)" ...

  20. ,"West Virginia Natural Gas Gross Withdrawals (MMcf)"

    U.S. Energy Information Administration (EIA) Indexed Site

    AM" "Back to Contents","Data 1: West Virginia Natural Gas Gross Withdrawals (MMcf)" "Sourcekey","N9010WV2" "Date","West Virginia Natural Gas Gross Withdrawals (MMcf)" ...

  1. ,"New Mexico Natural Gas Gross Withdrawals (MMcf)"

    U.S. Energy Information Administration (EIA) Indexed Site

    9:51:59 AM" "Back to Contents","Data 1: New Mexico Natural Gas Gross Withdrawals (MMcf)" "Sourcekey","N9010NM2" "Date","New Mexico Natural Gas Gross Withdrawals (MMcf)" ...

  2. ,"North Dakota Natural Gas Gross Withdrawals (MMcf)"

    U.S. Energy Information Administration (EIA) Indexed Site

    ...2016 9:51:58 AM" "Back to Contents","Data 1: North Dakota Natural Gas Gross Withdrawals (MMcf)" "Sourcekey","N9010ND2" "Date","North Dakota Natural Gas Gross Withdrawals (MMcf)" ...

  3. Michael Gross | Photosynthetic Antenna Research Center

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Michael Gross Michael Gross Michael Gross Principal Investigator E-mail: mgross@wustl.edu Phone: (314) 935-4814 Website: Washington University in St. Louis Principal Investigator Dr. Gross's research interests include analytical chemistry, biological chemistry, biophysical chemistry, FT-ICR instrument development, MALDI matrix development, mass spectrometry for protein biochemistry and biophysics, modified DNA and cancer, physical organic chemistry, protein and peptide analysis, and proteomics.

  4. Alaska--State Offshore Natural Gas Gross Withdrawals (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Gross Withdrawals (Million Cubic Feet) Alaska--State Offshore Natural Gas Gross ... Release Date: 06302016 Next Release Date: 07292016 Referring Pages: Offshore Gross ...

  5. US--Federal Offshore Natural Gas Gross Withdrawals (Million Cubic...

    U.S. Energy Information Administration (EIA) Indexed Site

    Gross Withdrawals (Million Cubic Feet) US--Federal Offshore Natural Gas Gross Withdrawals ... Release Date: 06302016 Next Release Date: 07292016 Referring Pages: Offshore Gross ...

  6. Louisiana--State Offshore Natural Gas Gross Withdrawals (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Gross Withdrawals (Million Cubic Feet) Louisiana--State Offshore Natural Gas Gross ... Release Date: 06302016 Next Release Date: 07292016 Referring Pages: Offshore Gross ...

  7. Federal Offshore--Alabama Natural Gas Gross Withdrawals (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Gross Withdrawals (Million Cubic Feet) Federal Offshore--Alabama Natural Gas Gross ... Release Date: 06302016 Next Release Date: 07292016 Referring Pages: Offshore Gross ...

  8. Texas--State Offshore Natural Gas Gross Withdrawals (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Gross Withdrawals (Million Cubic Feet) Texas--State Offshore Natural Gas Gross Withdrawals ... Release Date: 06302016 Next Release Date: 07292016 Referring Pages: Offshore Gross ...

  9. Federal Offshore--Texas Natural Gas Gross Withdrawals (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Gross Withdrawals (Million Cubic Feet) Federal Offshore--Texas Natural Gas Gross ... Release Date: 06302016 Next Release Date: 07292016 Referring Pages: Offshore Gross ...

  10. US--State Offshore Natural Gas Gross Withdrawals (Million Cubic...

    U.S. Energy Information Administration (EIA) Indexed Site

    Gross Withdrawals (Million Cubic Feet) US--State Offshore Natural Gas Gross Withdrawals ... Release Date: 06302016 Next Release Date: 07292016 Referring Pages: Offshore Gross ...

  11. Alabama--State Offshore Natural Gas Gross Withdrawals (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Gross Withdrawals (Million Cubic Feet) Alabama--State Offshore Natural Gas Gross ... Release Date: 06302016 Next Release Date: 07292016 Referring Pages: Offshore Gross ...

  12. Federal Offshore--Louisiana Natural Gas Gross Withdrawals (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Gross Withdrawals (Million Cubic Feet) Federal Offshore--Louisiana Natural Gas Gross ... Release Date: 06302016 Next Release Date: 07292016 Referring Pages: Offshore Gross ...

  13. Projecting household energy consumption within a conditional demand framework

    SciTech Connect (OSTI)

    Teotia, A.; Poyer, D.

    1991-01-01

    Few models attempt to assess and project household energy consumption and expenditure by taking into account differential household choices correlated with such variables as race, ethnicity, income, and geographic location. The Minority Energy Assessment Model (MEAM), developed by Argonne National Laboratory (ANL) for the US Department of Energy (DOE), provides a framework to forecast the energy consumption and expenditure of majority, black, Hispanic, poor, and nonpoor households. Among other variables, household energy demand for each of these population groups in MEAM is affected by housing factors (such as home age, home ownership, home type, type of heating fuel, and installed central air conditioning unit), demographic factors (such as household members and urban/rural location), and climate factors (such as heating degree days and cooling degree days). The welfare implications of the revealed consumption patterns by households are also forecast. The paper provides an overview of the model methodology and its application in projecting household energy consumption under alternative energy scenarios developed by Data Resources, Inc., (DRI).

  14. Projecting household energy consumption within a conditional demand framework

    SciTech Connect (OSTI)

    Teotia, A.; Poyer, D.

    1991-12-31

    Few models attempt to assess and project household energy consumption and expenditure by taking into account differential household choices correlated with such variables as race, ethnicity, income, and geographic location. The Minority Energy Assessment Model (MEAM), developed by Argonne National Laboratory (ANL) for the US Department of Energy (DOE), provides a framework to forecast the energy consumption and expenditure of majority, black, Hispanic, poor, and nonpoor households. Among other variables, household energy demand for each of these population groups in MEAM is affected by housing factors (such as home age, home ownership, home type, type of heating fuel, and installed central air conditioning unit), demographic factors (such as household members and urban/rural location), and climate factors (such as heating degree days and cooling degree days). The welfare implications of the revealed consumption patterns by households are also forecast. The paper provides an overview of the model methodology and its application in projecting household energy consumption under alternative energy scenarios developed by Data Resources, Inc., (DRI).

  15. Table 5.9. U.S. Average Vehicle-Miles Traveled by Family Income...

    U.S. Energy Information Administration (EIA) Indexed Site

    1993 Household Characteristics RSE Column Factor: Total 1993 Family Income Below Poverty Line Eli- gible for Fed- eral Assist- ance 1 RSE Row Factor: Less than 5,000 5,000...

  16. Total Natural Gas Gross Withdrawals (Summary)

    U.S. Energy Information Administration (EIA) Indexed Site

    Pipeline and Distribution Use Price Citygate Price Residential Price Commercial Price Industrial Price Vehicle Fuel Price Electric Power Price Proved Reserves as of 12/31 Reserves Adjustments Reserves Revision Increases Reserves Revision Decreases Reserves Sales Reserves Acquisitions Reserves Extensions Reserves New Field Discoveries New Reservoir Discoveries in Old Fields Estimated Production Number of Producing Gas Wells Gross Withdrawals Gross Withdrawals From Gas Wells Gross Withdrawals From

  17. ,"Illinois Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    ...ame","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Illinois Natural Gas Gross Withdrawals and Production",10,"Monthly","42016","01151991" ,"Release ...

  18. ,"Oregon Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Oregon Natural Gas Gross Withdrawals and Production",10,"Monthly","42016","01151991" ,"Release ...

  19. ,"California Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Of Series","Frequency","Latest Data for" ,"Data 1","California Natural Gas Gross Withdrawals and Production",10,"Monthly","42016","01151989" ,"Release ...

  20. ,"Louisiana Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Of Series","Frequency","Latest Data for" ,"Data 1","Louisiana Natural Gas Gross Withdrawals and Production",10,"Monthly","42016","01151989" ,"Release ...

  1. ,"Oklahoma Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    ...ame","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Oklahoma Natural Gas Gross Withdrawals and Production",10,"Monthly","42016","01151989" ,"Release ...

  2. ,"Pennsylvania Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Of Series","Frequency","Latest Data for" ,"Data 1","Pennsylvania Natural Gas Gross Withdrawals and Production",10,"Monthly","42016","01151991" ,"Release ...

  3. ,"Colorado Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    ...ame","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Colorado Natural Gas Gross Withdrawals and Production",10,"Monthly","42016","01151989" ,"Release ...

  4. ,"Florida Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Florida Natural Gas Gross Withdrawals and Production",10,"Monthly","42016","01151989" ,"Release ...

  5. ,"Utah Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Utah Natural Gas Gross Withdrawals and Production",10,"Monthly","42016","01151989" ,"Release ...

  6. ,"Montana Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Montana Natural Gas Gross Withdrawals and Production",10,"Monthly","42016","01151989" ,"Release ...

  7. ,"Kansas Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Kansas Natural Gas Gross Withdrawals and Production",10,"Monthly","42016","01151989" ,"Release ...

  8. ,"Texas Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Texas Natural Gas Gross Withdrawals and Production",10,"Monthly","42016","01151989" ,"Release ...

  9. ,"Texas Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Texas Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  10. ,"Kansas Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Kansas Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  11. ,"Pennsylvania Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Pennsylvania Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  12. ,"Kentucky Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Kentucky Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  13. ,"Oregon Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Oregon Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301979" ,"Release...

  14. ,"Virginia Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Virginia Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  15. ,"Missouri Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Missouri Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  16. ,"Illinois Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Illinois Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  17. ,"Florida Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Florida Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  18. ,"Utah Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Utah Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  19. ,"Indiana Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Indiana Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  20. ,"Nevada Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Nevada Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301991" ,"Release...

  1. ,"Montana Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Montana Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  2. ,"Ohio Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Ohio Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  3. ,"California Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","California Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  4. ,"Mississippi Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Mississippi Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  5. ,"Nebraska Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Nebraska Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  6. ,"Michigan Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Michigan Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  7. ,"Tennessee Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Tennessee Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  8. ,"Oklahoma Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Oklahoma Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  9. ,"Wyoming Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Wyoming Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  10. ,"Maryland Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Maryland Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  11. ,"Louisiana Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Louisiana Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  12. ,"Colorado Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Colorado Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  13. David J. Gross and the Strong Force

    Office of Scientific and Technical Information (OSTI)

    from Cal Alum David Gross (PhD '66) Shares Nobel Prize in Physics, University of California Berkeley Resources with Additional Information Additional information about David ...

  14. David J. Gross and the Strong Force

    Office of Scientific and Technical Information (OSTI)

    published their proposal simultaneously with H. David Politzer, a graduate student at Harvard University who independently came up with the same idea. ... The discovery of Gross,...

  15. ,"Wyoming Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Wyoming Natural Gas Gross Withdrawals and Production",10,"Monthly","32016","01151989" ,"Release ...

  16. Energy-efficient housing alternatives: a predictive model of factors affecting household perceptions

    SciTech Connect (OSTI)

    Schreckengost, R.L.

    1985-01-01

    The major purpose of this investigation was to assess the impact of household socio-economic factors, dwelling characteristics, energy conservation behavior, and energy attitudes on the perceptions of energy-efficient housing alternatives. Perceptions of passive solar, active solar, earth sheltered, and retrofitted housing were examined. Data used were from the Southern Regional Research Project, S-141, Housing for Low and Moderate Income Families. Responses from 1804 households living in seven southern states were analyzed. A conceptual model was proposed to test the hypothesized relationships which were examined by path analysis. Perceptions of energy efficient housing alternatives were found to be a function of selected household and dwelling characteristics, energy attitude, household economic factors, and household conservation behavior. Age and education of the respondent, family size, housing-income ratio, utility income ratio, energy attitude, and size of the dwelling unit were found to have direct and indirect effects on perceptions of energy-efficient housing alternatives. Energy conservation behavior made a significant direct impact with behavioral energy conservation changes having the most profound influence. Conservation behavior was influenced by selected household and dwelling characteristics, energy attitude, and household economic factors.

  17. Buildings Energy Data Book: 2.9 Low-Income Housing

    Buildings Energy Data Book [EERE]

    2 Energy Burden Definitions Energy burden is an important statistic for policy makers who are considering the need for energy assistance. Energy burden can be defined broadly as the burden placed on household incomes by the cost of energy, or more simply, the ratio of energy expenditures to household income. However, there are different ways to compute energy burden, and different interpretations and uses of the energy burden statistics. DOE Weatherization primarily uses mean individual burden

  18. Household Vehicles Energy Consumption 1991

    U.S. Energy Information Administration (EIA) Indexed Site

    or commercial trucks (See Table 1). Energy Information AdministrationHousehold Vehicles Energy Consumption 1991 5 The 1991 RTECS count includes vehicles that were owned or used...

  19. Household Vehicles Energy Consumption 1991

    U.S. Energy Information Administration (EIA) Indexed Site

    logo printer-friendly version logo for Portable Document Format file Household Vehicles Energy Consumption 1991 December 1993 Release Next Update: August 1997. Based on the 1991...

  20. ,"Arizona Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    ,,"(202) 586-8800",,,"06292016 10:51:24 AM" "Back to Contents","Data 1: Arizona Natural Gas Gross Withdrawals and Production" "Sourcekey","N9010AZ2","N9011AZ2","N9012AZ2","NGME...

  1. ,"Arkansas Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    ,,"(202) 586-8800",,,"06292016 10:51:23 AM" "Back to Contents","Data 1: Arkansas Natural Gas Gross Withdrawals and Production" "Sourcekey","N9010AR2","N9011AR2","N9012AR2","NGME...

  2. ,"Arizona Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    ,,"(202) 586-8800",,,"06292016 10:51:23 AM" "Back to Contents","Data 1: Arizona Natural Gas Gross Withdrawals and Production" "Sourcekey","N9010AZ2","N9011AZ2","N9012AZ2","NGME...

  3. ,"Alabama Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    ,,"(202) 586-8800",,,"06292016 10:51:21 AM" "Back to Contents","Data 1: Alabama Natural Gas Gross Withdrawals and Production" "Sourcekey","N9010AL2","N9011AL2","N9012AL2","NGME...

  4. ,"Alaska Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    ,,"(202) 586-8800",,,"4292016 6:48:19 AM" "Back to Contents","Data 1: Alaska Natural Gas Gross Withdrawals and Production" "Sourcekey","N9010AK2","N9011AK2","N9012AK2","NGME...

  5. ,"New York Natural Gas Gross Withdrawals (MMcf)"

    U.S. Energy Information Administration (EIA) Indexed Site

    ,,"(202) 586-8800",,,"12152015 12:10:48 PM" "Back to Contents","Data 1: New York Natural Gas Gross Withdrawals (MMcf)" "Sourcekey","N9010NY2" "Date","New York...

  6. Quantification of the Potential Gross Economic Impacts of Five...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Quantification of the Potential Gross Economic Impacts of Five Methane Reduction Scenarios Quantification of the Potential Gross Economic Impacts of Five Methane Reduction Scenarios ...

  7. Property:DailyOpWaterUseGross | Open Energy Information

    Open Energy Info (EERE)

    Property Name DailyOpWaterUseGross Property Type Number Description Daily Operation Water Use (afday) Gross. Retrieved from "http:en.openei.orgwindex.php?titleProperty:...

  8. Federal Offshore--Gulf of Mexico Natural Gas Gross Withdrawals...

    U.S. Energy Information Administration (EIA) Indexed Site

    Release Date: 06302016 Next Release Date: 07292016 Referring Pages: Natural Gas Gross Withdrawals from Shale Gas Wells Federal Offshore Gulf of Mexico Natural Gas Gross ...

  9. ,"US--Federal Offshore Natural Gas Gross Withdrawals (MMcf)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Federal Offshore Natural Gas Gross Withdrawals (MMcf)" ,"Click worksheet name or tab at ... Data for" ,"Data 1","US--Federal Offshore Natural Gas Gross Withdrawals ...

  10. ,"Texas--State Offshore Natural Gas Gross Withdrawals (MMcf)...

    U.S. Energy Information Administration (EIA) Indexed Site

    Data for" ,"Data 1","Texas--State Offshore Natural Gas Gross Withdrawals ... "Back to Contents","Data 1: Texas--State Offshore Natural Gas Gross Withdrawals (MMcf)" ...

  11. ,"Federal Offshore--Texas Natural Gas Gross Withdrawals (MMcf...

    U.S. Energy Information Administration (EIA) Indexed Site

    Data for" ,"Data 1","Federal Offshore--Texas Natural Gas Gross Withdrawals ... AM" "Back to Contents","Data 1: Federal Offshore--Texas Natural Gas Gross Withdrawals ...

  12. ,"US--State Offshore Natural Gas Gross Withdrawals (MMcf)"

    U.S. Energy Information Administration (EIA) Indexed Site

    State Offshore Natural Gas Gross Withdrawals (MMcf)" ,"Click worksheet name or tab at ... Data for" ,"Data 1","US--State Offshore Natural Gas Gross Withdrawals ...

  13. ,"Federal Offshore--Alabama Natural Gas Gross Withdrawals (MMcf...

    U.S. Energy Information Administration (EIA) Indexed Site

    Data for" ,"Data 1","Federal Offshore--Alabama Natural Gas Gross Withdrawals ... AM" "Back to Contents","Data 1: Federal Offshore--Alabama Natural Gas Gross Withdrawals ...

  14. ,"Louisiana--State Offshore Natural Gas Gross Withdrawals (MMcf...

    U.S. Energy Information Administration (EIA) Indexed Site

    Data for" ,"Data 1","Louisiana--State Offshore Natural Gas Gross Withdrawals ... to Contents","Data 1: Louisiana--State Offshore Natural Gas Gross Withdrawals (MMcf)" ...

  15. ,"Alaska--State Offshore Natural Gas Gross Withdrawals (MMcf...

    U.S. Energy Information Administration (EIA) Indexed Site

    Data for" ,"Data 1","Alaska--State Offshore Natural Gas Gross Withdrawals ... to Contents","Data 1: Alaska--State Offshore Natural Gas Gross Withdrawals (MMcf)" ...

  16. Federal Offshore--Gulf of Mexico Natural Gas Gross Withdrawals...

    U.S. Energy Information Administration (EIA) Indexed Site

    Release Date: 06302016 Next Release Date: 07292016 Referring Pages: Natural Gas Gross Withdrawals from Coalbed Wells Federal Offshore Gulf of Mexico Natural Gas Gross ...

  17. ,"Federal Offshore--Louisiana Natural Gas Gross Withdrawals ...

    U.S. Energy Information Administration (EIA) Indexed Site

    Data for" ,"Data 1","Federal Offshore--Louisiana Natural Gas Gross Withdrawals ... AM" "Back to Contents","Data 1: Federal Offshore--Louisiana Natural Gas Gross Withdrawals ...

  18. ,"Alabama--State Offshore Natural Gas Gross Withdrawals (MMcf...

    U.S. Energy Information Administration (EIA) Indexed Site

    Data for" ,"Data 1","Alabama--State Offshore Natural Gas Gross Withdrawals ... to Contents","Data 1: Alabama--State Offshore Natural Gas Gross Withdrawals (MMcf)" ...

  19. ,"Federal Offshore Gulf of Mexico Natural Gas Gross Withdrawals...

    U.S. Energy Information Administration (EIA) Indexed Site

    Gulf of Mexico Natural Gas Gross Withdrawals and Production" ,"Click worksheet name or tab ... for" ,"Data 1","Federal Offshore Gulf of Mexico Natural Gas Gross Withdrawals and ...

  20. ,"Texas Natural Gas Gross Withdrawals Total Offshore (MMcf)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Data for" ,"Data 1","Texas Natural Gas Gross Withdrawals Total ... 7:03:02 AM" "Back to Contents","Data 1: Texas Natural Gas Gross Withdrawals Total ...

  1. BC Hydro Brings Energy Savings to Low-Income Families in Canada |

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Department of Energy BC Hydro Brings Energy Savings to Low-Income Families in Canada BC Hydro Brings Energy Savings to Low-Income Families in Canada The number of British Columbia, Canada, households eligible for Better Buildings Residential Network member BC Hydro's Energy Conservation Assistance Program (ECAP) just doubled. British Columbia Energy Minister Bill Bennett recently announced an increase in the low-income qualification cutoff for BC Hydro's free home energy-saving kits and

  2. Household vehicles energy consumption 1994

    SciTech Connect (OSTI)

    1997-08-01

    Household Vehicles Energy Consumption 1994 reports on the results of the 1994 Residential Transportation Energy Consumption Survey (RTECS). The RTECS is a national sample survey that has been conducted every 3 years since 1985. For the 1994 survey, more than 3,000 households that own or use some 6,000 vehicles provided information to describe vehicle stock, vehicle-miles traveled, energy end-use consumption, and energy expenditures for personal vehicles. The survey results represent the characteristics of the 84.9 million households that used or had access to vehicles in 1994 nationwide. (An additional 12 million households neither owned or had access to vehicles during the survey year.) To be included in then RTECS survey, vehicles must be either owned or used by household members on a regular basis for personal transportation, or owned by a company rather than a household, but kept at home, regularly available for the use of household members. Most vehicles included in the RTECS are classified as {open_quotes}light-duty vehicles{close_quotes} (weighing less than 8,500 pounds). However, the RTECS also includes a very small number of {open_quotes}other{close_quotes} vehicles, such as motor homes and larger trucks that are available for personal use.

  3. Household Vehicles Energy Use Cover Page

    U.S. Energy Information Administration (EIA) Indexed Site

    Energy Use Cover Page Glossary Home > Households, Buildings & Industry >Transportation Surveys > Household Vehicles Energy Use Cover Page Contact Us * Feedback * PrivacySecurity *...

  4. Strategies for Collecting Household Energy Data | Department...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Collecting Household Energy Data Strategies for Collecting Household Energy Data Better Buildings Neighborhood Program Data and Evaluation Peer Exchange Call: Strategies for ...

  5. Next Generation Household Refrigerator | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Next Generation Household Refrigerator Next Generation Household Refrigerator Embraco's high efficiency, oil-free linear compressor.
    Credit: Whirlpool Embraco's high ...

  6. ac_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    0a. Air Conditioning by Midwest Census Region, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. Midwest Census Region RSE Row Factors Total Census Division East North Central West North Central 0.5 1.0 1.2 1.4 Households With Electric Air-Conditioning Equipment ...................... 82.9 20.5 13.6 6.8 2.2 Air Conditioners Not Used ........................... 2.1 0.3 Q Q 27.5 Households Using Electric Air-Conditioning 1

  7. ac_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    1a. Air Conditioning by South Census Region, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. South Census Region RSE Row Factors Total Census Division South Atlantic East South Central West South Central 0.5 0.8 1.2 1.3 1.4 Households With Electric Air-Conditioning Equipment ...................... 82.9 37.2 19.3 6.4 11.5 1.5 Air Conditioners Not Used ........................... 2.1 0.4 Q Q Q 28.2 Households Using Electric Air-Conditioning 1

  8. ac_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    2a. Air Conditioning by West Census Region, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total Census Division Mountain Pacific 0.4 1.2 1.7 1.4 Households With Electric Air-Conditioning Equipment ...................... 82.9 10.7 3.4 7.2 7.1 Air Conditioners Not Used ........................... 2.1 1.1 0.2 0.9 15.5 Households Using Electric Air-Conditioning 1 ........................................ 80.8 9.6 3.2

  9. ac_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    4a. Air Conditioning by Type of Housing Unit, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Type of Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.4 0.6 1.5 1.4 1.8 Households With Electric Air-Conditioning Equipment ........ 82.9 58.7 6.5 12.4 5.3 4.9 Air Conditioners Not Used ............ 2.1 1.1 Q 0.6 Q 21.8 Households Using Electric Air-Conditioning 1

  10. ac_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    8a. Air Conditioning by Urban/Rural Location, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Urban/Rural Location 1 RSE Row Factors City Town Suburbs Rural 0.5 0.8 1.4 1.3 1.4 Households With Electric Air-Conditioning Equipment ...................... 82.9 36.8 13.6 18.9 13.6 4.3 Air Conditioners Not Used ........................... 2.1 1.2 0.2 0.4 0.3 21.4 Households Using Electric Air-Conditioning 2 ........................................ 80.8 35.6 13.4

  11. ac_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    9a. Air Conditioning by Northeast Census Region, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.0 1.2 1.8 Households With Electric Air-Conditioning Equipment ...................... 82.9 14.5 11.3 3.2 3.3 Air Conditioners Not Used ........................... 2.1 0.3 0.3 Q 28.3 Households Using Electric Air-Conditioning 1

  12. Household Vehicles Energy Consumption 1991

    U.S. Energy Information Administration (EIA) Indexed Site

    16.8 17.4 18.6 18.9 1.7 2.2 0.6 1.5 Energy Information AdministrationHousehold Vehicles Energy Consumption 1991 15 Vehicle Miles Traveled per Vehicle (Thousand) . . . . . . . . ....

  13. char_household2001.pdf

    Annual Energy Outlook [U.S. Energy Information Administration (EIA)]

    Contact: Stephanie J. Battles, Survey Manager (stephanie.battles@eia.doe.gov) World Wide Web: http:www.eia.doe.govemeuconsumption Table HC2-1a. Household Characteristics by ...

  14. Cover Page of Household Vehicles Energy Use: Latest Data & Trends

    Gasoline and Diesel Fuel Update (EIA)

    Household Vehicles Energy Use Cover Page Cover Page of Household Vehicles Energy Use: Latest Data & Trends...

  15. char_household2001.pdf

    Gasoline and Diesel Fuel Update (EIA)

    Income Relative to Poverty Line Below 100 Percent ...... definition. 2 Below 150 percent of poverty line or 60 percent of median State ...

  16. Low Income Efficiency

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Materials Meeting 5, November 5, 2015 in Portland, Oregon Agenda BPA Low Income Benchmarking and October 2015 IM Updates Presentation Side by Side Comparison of BPA Measures...

  17. Oregon Natural Gas Gross Withdrawals and Production

    U.S. Energy Information Administration (EIA) Indexed Site

    2012 2013 2014 View History Gross Withdrawals 821 1,407 1,344 770 770 950 1979-2014 From Gas Wells 821 1,407 1,344 770 770 950 1979-2014 From Oil Wells 0 0 0 0 0 0 1996-2014 From ...

  18. Federal options for low-income electricity policy

    SciTech Connect (OSTI)

    Baxter, L.W.

    1998-06-01

    Protection of low-income consumers remains an important public policy concern in a restructuring electricity industry. Policies are needed to ensure that low-income households have enough affordable electricity to protect their health and safety, and that they are not victimized by unscrupulous suppliers. In this paper, the author presents three broad federal roles in setting low-income electricity policy, and discuss three more specific policy areas: universal service, electricity assistance, and health and safety. He discusses the key policy issues that arise when considering these potential federal initiatives and draw upon reviews of proposed low-income policies from restructuring proposals in eight states--California, Massachusetts, New Hampshire, New York, Pennsylvania, Rhode Island, Vermont, and Wisconsin.

  19. Resource handbook for low-income residential retrofits

    SciTech Connect (OSTI)

    Callaway, J.W.; Brenchley, D.L.; Davis, L.J.; Ivey, D.L.; Smith, S.A.; Westergard, E.J.

    1987-04-01

    The purpose of the handbook is to provide technical assistance to state grantees participating in the Partnerships in Low-Income Residential Retrofit (PILIRR) Program. PILIRR is a demonstration program aimed at identifying innovative, successful approaches to developing public and private support for weatherization of low-income households. The program reflects the basic concept that responsibility for financial support for conservation activities such as low-income residential retrofitting is likely to gradually shift from the DOE to the states and the private sector. In preparing the handbook, PNL staff surveyed over 50 programs that provide assistance to low-income residents. The survey provided information on factors that contribute to successful programs. PNL also studied the winning PILIRR proposals (from the states of Florida, Iowa, Kentucky, Oklahoma and Washington) and identified the approaches proposed and the type of information that would be most helpful in implementing these approaches.

  20. ac_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    2a. Air Conditioning by Year of Construction, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Year of Construction RSE Row Factors 1990 to 2001 1 1980 to 1989 1970 to 1979 1960 to 1969 1950 to 1959 1949 or Before 0.4 1.6 1.2 1.1 1.2 1.1 0.9 Households With Electric Air-Conditioning Equipment ........ 82.9 13.6 16.0 14.7 10.4 10.5 17.6 4.7 Air Conditioners Not Used ............ 2.1 Q 0.3 0.5 0.3 0.4 0.5 27.2 Households Using Electric Air-Conditioning 2

  1. ac_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    5a. Air Conditioning by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Owner- Occupied Units Type of Owner-Occupied Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.5 0.5 1.5 1.4 1.8 Households With Electric Air-Conditioning Equipment ........ 59.5 58.7 6.5 12.4 5.3 5.2 Air Conditioners Not Used ............ 1.2 1.1 Q 0.6 Q 23.3 Households Using

  2. ac_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    6a. Air Conditioning by Type of Rented Housing Unit, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Rented Units Type of Rented Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.8 0.5 1.4 1.2 1.6 Households With Electric Air-Conditioning Equipment ........ 23.4 58.7 6.5 12.4 5.3 6.1 Air Conditioners Not Used ............ 0.9 1.1 Q 0.6 Q 23.0 Households Using Electric Air-Conditioning

  3. homeoffice_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    0a. Home Office Equipment by Midwest Census Region, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total U.S. Midwest Census Region RSE Row Factors Total Census Division East North Central West North Central 0.5 1.0 1.2 1.6 Total .............................................................. 107.0 24.5 17.1 7.4 NE Households Using Office Equipment ......................................... 96.2 22.4 15.7 6.7 1.3 Personal Computers 1 ................................. 60.0

  4. homeoffice_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    1a. Home Office Equipment by South Census Region, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total U.S. South Census Region RSE Row Factors Total Census Division South Atlantic East South Central West South Central 0.5 0.8 1.2 1.3 1.6 Total .............................................................. 107.0 38.9 20.3 6.8 11.8 NE Households Using Office Equipment ......................................... 96.2 34.6 18.4 6.0 10.1 1.2 Personal Computers 1

  5. homeoffice_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    2a. Home Office Equipment by West Census Region, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total Census Division Mountain Pacific 0.5 1.0 1.6 1.2 Total .............................................................. 107.0 23.3 6.7 16.6 NE Households Using Office Equipment ......................................... 96.2 21.4 6.2 15.2 1.0 Personal Computers 1 ................................. 60.0 14.3 4.0 10.4 3.7 Number of

  6. homeoffice_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    9a. Home Office Equipment by Northeast Census Region, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.1 1.4 1.2 Total .............................................................. 107.0 20.3 14.8 5.4 NE Households Using Office Equipment ......................................... 96.2 17.9 12.8 5.0 1.3 Personal Computers 1 ................................. 60.0 10.9

  7. Buildings Energy Data Book: 2.9 Low-Income Housing

    Buildings Energy Data Book [EERE]

    4 Weatherization Population Facts - Roughly 25% of Federally eligible households move in and out of poverty "classification" each year. - The average income of Federally eligible households in FY 2005 was $16,264, based on RECS and Bureau of the Census' Current Population Survey (CPS) data. - States target the neediest, especially the elderly, persons with disabilities, and families with children. - Since the inception of the Weatherization Assistance Program in 1976, over 6.3 million

  8. Household energy use in urban Venezuela: Implications from surveys in Maracaibo, Valencia, Merida, and Barcelona-Puerto La Cruz

    SciTech Connect (OSTI)

    Figueroa, M.J.; Sathaye, J.

    1993-08-01

    This report identifies the most important results of a comparative analysis of household commercial energy use in Venezuelan urban cities. The use of modern fuels is widespread among all cities. Cooking consumes the largest share of urban household energy use. The survey documents no use of biomass and a negligible use of kerosene for cooking. LPG, natural gas, and kerosene are the main fuels available. LPG is the fuel choice of low-income households in all cities except Maracaibo, where 40% of all households use natural gas. Electricity consumption in Venezuela`s urban households is remarkably high compared with the levels used in households in comparable Latin American countries and in households of industrialized nations which confront harsher climatic conditions and, therefore, use electricity for water and space heating. The penetration of appliances in Venezuela`s urban households is very high. The appliances available on the market are inefficient, and there are inefficient patterns of energy use among the population. Climate conditions and the urban built form all play important roles in determining the high level of energy consumption in Venezuelan urban households. It is important to acknowledge the opportunities for introducing energy efficiency and conservation in Venezuela`s residential sector, particularly given current economic and financial constraints, which may hamper the future provision of energy services.

  9. char_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    Income Relative to Poverty Line Below 100 Percent ...... 0.9 0.5 0.6 13.0 1 Below 150 percent of poverty line or 60 percent of median State ...

  10. char_household2001.pdf

    Annual Energy Outlook [U.S. Energy Information Administration (EIA)]

    Income Relative to Poverty Line Below 100 Percent ...... 0.6 0.5 Q 17.4 1 Below 150 percent of poverty line or 60 percent of median State ...

  11. char_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    Income Relative to Poverty Line Below 100 Percent ...... 15.0 1.4 2.3 ... were conducted. 2 Below 150 percent of poverty line or 60 percent of median State ...

  12. char_household2001.pdf

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Income Relative to Poverty Line Below 100 Percent ...... 0.7 0.4 0.2 18.4 1 Below 150 percent of poverty line or 60 percent of median State ...

  13. char_household2001.pdf

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Income Relative to Poverty Line Below 100 Percent ...... 15.0 1.0 3.4 ... weather station. 2 Below 150 percent of poverty line or 60 percent of median State ...

  14. char_household2001.pdf

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Income Relative to Poverty Line Below 100 Percent ...... 1.2 0.7 0.5 11.3 1 Below 150 percent of poverty line or 60 percent of median State ...

  15. char_household2001.pdf

    Gasoline and Diesel Fuel Update (EIA)

    Income Relative to Poverty Line Below 100 Percent ...... 1.5 0.5 1.0 14.6 1 Below 150 percent of poverty line or 60 percent of median State ...

  16. Fact #748: October 8, 2012 Components of Household Expenditures...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Household Expenditures on Transportation, 1984-2010 Fact 748: October 8, 2012 Components of Household Expenditures on Transportation, 1984-2010 The overall share of annual household ...

  17. Missouri Natural Gas Gross Withdrawals from Oil Wells (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Oil Wells (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1991 0 ... Referring Pages: Natural Gas Gross Withdrawals from Oil Wells Missouri Natural Gas Gross ...

  18. Virginia Natural Gas Gross Withdrawals (Million Cubic Feet per...

    Annual Energy Outlook [U.S. Energy Information Administration (EIA)]

    Gross Withdrawals (Million Cubic Feet per Day) Virginia Natural Gas Gross Withdrawals (Million Cubic Feet per Day) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2006 271 275...

  19. ,"Nevada Natural Gas Gross Withdrawals from Shale Gas (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Data for" ,"Data 1","Nevada Natural Gas Gross Withdrawals from Shale ... 1:29:33 AM" "Back to Contents","Data 1: Nevada Natural Gas Gross Withdrawals from Shale ...

  20. ,"U.S. Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    6:48:07 AM" "Back to Contents","Data 1: U.S. Natural Gas Gross Withdrawals and ...2","N9030US2","N9050US2","N9070US2" "Date","U.S. Natural Gas Gross Withdrawals ...

  1. ,"U.S. Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    1:00:33 PM" "Back to Contents","Data 1: U.S. Natural Gas Gross Withdrawals and ...2","N9030US2","N9050US2","N9070US2" "Date","U.S. Natural Gas Gross Withdrawals ...

  2. West Virginia Natural Gas Gross Withdrawals (Million Cubic Feet...

    Gasoline and Diesel Fuel Update (EIA)

    Gross Withdrawals (Million Cubic Feet per Day) West Virginia Natural Gas Gross Withdrawals (Million Cubic Feet per Day) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2006...

  3. Montana Natural Gas Gross Withdrawals (Million Cubic Feet per...

    Gasoline and Diesel Fuel Update (EIA)

    Gross Withdrawals (Million Cubic Feet per Day) Montana Natural Gas Gross Withdrawals (Million Cubic Feet per Day) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2006 317 313...

  4. California Natural Gas Gross Withdrawals (Million Cubic Feet...

    Gasoline and Diesel Fuel Update (EIA)

    Gross Withdrawals (Million Cubic Feet per Day) California Natural Gas Gross Withdrawals (Million Cubic Feet per Day) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2006 998...

  5. ,"New Mexico Natural Gas Gross Withdrawals from Oil Wells (MMcf...

    U.S. Energy Information Administration (EIA) Indexed Site

    ...","Frequency","Latest Data for" ,"Data 1","New Mexico Natural Gas Gross Withdrawals from ... 10:10:49 AM" "Back to Contents","Data 1: New Mexico Natural Gas Gross Withdrawals from ...

  6. ,"New Mexico Natural Gas Gross Withdrawals from Shale Gas (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    ...","Frequency","Latest Data for" ,"Data 1","New Mexico Natural Gas Gross Withdrawals from ... 10:13:23 AM" "Back to Contents","Data 1: New Mexico Natural Gas Gross Withdrawals from ...

  7. ,"New Mexico Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    ...","Frequency","Latest Data for" ,"Data 1","New Mexico Natural Gas Gross Withdrawals and ... 8:15:20 AM" "Back to Contents","Data 1: New Mexico Natural Gas Gross Withdrawals and ...

  8. ,"New Mexico Natural Gas Gross Withdrawals from Gas Wells (MMcf...

    U.S. Energy Information Administration (EIA) Indexed Site

    ...","Frequency","Latest Data for" ,"Data 1","New Mexico Natural Gas Gross Withdrawals from ... 10:10:30 AM" "Back to Contents","Data 1: New Mexico Natural Gas Gross Withdrawals from ...

  9. ,"New York Natural Gas Gross Withdrawals from Shale Gas (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    ...","Frequency","Latest Data for" ,"Data 1","New York Natural Gas Gross Withdrawals from ... 10:13:24 AM" "Back to Contents","Data 1: New York Natural Gas Gross Withdrawals from ...

  10. Kansas Natural Gas Gross Withdrawals (Million Cubic Feet per...

    Annual Energy Outlook [U.S. Energy Information Administration (EIA)]

    Gross Withdrawals (Million Cubic Feet per Day) Kansas Natural Gas Gross Withdrawals (Million Cubic Feet per Day) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2006 1,049...

  11. Arizona Natural Gas Gross Withdrawals (Million Cubic Feet per...

    Annual Energy Outlook [U.S. Energy Information Administration (EIA)]

    Arizona Natural Gas Gross Withdrawals (Million Cubic Feet per Day) Arizona Natural Gas Gross Withdrawals (Million Cubic Feet per Day) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct...

  12. New York Natural Gas Gross Withdrawals (Million Cubic Feet per...

    Gasoline and Diesel Fuel Update (EIA)

    Gross Withdrawals (Million Cubic Feet per Day) New York Natural Gas Gross Withdrawals (Million Cubic Feet per Day) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2006 149 147...

  13. Federal Offshore--Gulf of Mexico Natural Gas Gross Withdrawals...

    Gasoline and Diesel Fuel Update (EIA)

    Federal Offshore--Gulf of Mexico Natural Gas Gross Withdrawals (Million Cubic Feet per Day) Federal Offshore--Gulf of Mexico Natural Gas Gross Withdrawals (Million Cubic Feet per...

  14. ,"Kansas Natural Gas Gross Withdrawals from Shale Gas (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Data for" ,"Data 1","Kansas Natural Gas Gross Withdrawals from Shale ... 7:12:26 AM" "Back to Contents","Data 1: Kansas Natural Gas Gross Withdrawals from Shale ...

  15. ,"North Dakota Natural Gas Gross Withdrawals from Oil Wells ...

    U.S. Energy Information Administration (EIA) Indexed Site

    Data for" ,"Data 1","North Dakota Natural Gas Gross Withdrawals from ... 9:52:34 AM" "Back to Contents","Data 1: North Dakota Natural Gas Gross Withdrawals from ...

  16. ,"North Dakota Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Data for" ,"Data 1","North Dakota Natural Gas Gross Withdrawals and ... 10:51:41 AM" "Back to Contents","Data 1: North Dakota Natural Gas Gross Withdrawals and ...

  17. ,"North Dakota Natural Gas Gross Withdrawals from Gas Wells ...

    U.S. Energy Information Administration (EIA) Indexed Site

    Data for" ,"Data 1","North Dakota Natural Gas Gross Withdrawals from ... 9:52:18 AM" "Back to Contents","Data 1: North Dakota Natural Gas Gross Withdrawals from ...

  18. ,"North Dakota Natural Gas Gross Withdrawals from Shale Gas ...

    U.S. Energy Information Administration (EIA) Indexed Site

    Data for" ,"Data 1","North Dakota Natural Gas Gross Withdrawals from ... 9:55:03 AM" "Back to Contents","Data 1: North Dakota Natural Gas Gross Withdrawals from ...

  19. New Mexico Natural Gas Gross Withdrawals (Million Cubic Feet...

    Annual Energy Outlook [U.S. Energy Information Administration (EIA)]

    Gross Withdrawals (Million Cubic Feet per Day) New Mexico Natural Gas Gross Withdrawals (Million Cubic Feet per Day) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2006 4,406...

  20. ,"Texas Natural Gas Gross Withdrawals from Shale Gas (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Data for" ,"Data 1","Texas Natural Gas Gross Withdrawals from Shale ... 7:12:29 AM" "Back to Contents","Data 1: Texas Natural Gas Gross Withdrawals from Shale ...

  1. ac_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. Four Most Populated States RSE Row Factors New York California Texas Florida 0.4 1.1 1.7 1.2 1.2 Households With Electric Air-Conditioning Equipment ...................... 82.9 4.9 6.0 7.4 6.2 2.4 Air Conditioners Not Used ........................... 2.1 0.1 0.8 Q 0.1 23.2 Households Using Electric Air-Conditioning 1 ........................................ 80.8 4.7 5.2 7.4 6.1 2.6 Type of Electric Air-Conditioning Used Central

  2. homeoffice_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    2a. Home Office Equipment by Year of Construction, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total Year of Construction RSE Row Factors 1990 to 2001 1 1980 to 1989 1970 to 1979 1960 to 1969 1950 to 1959 1949 or Before 0.4 1.4 1.1 1.1 1.2 1.2 1.0 Total ............................................... 107.0 15.5 18.2 18.8 13.8 14.2 26.6 4.2 Households Using Office Equipment .......................... 96.2 14.9 16.7 17.0 12.2 13.0 22.4 4.4 Personal Computers 2

  3. appl_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    2a. Appliances by West Census Region, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total Census Division Mountain Pacific 0.5 1.0 1.7 1.2 Total .............................................................. 107.0 23.3 6.7 16.6 NE Kitchen Appliances Cooking Appliances Oven ......................................................... 101.7 22.1 6.6 15.5 1.1 1

  4. char_household2001.pdf

    Gasoline and Diesel Fuel Update (EIA)

    Income Relative to Poverty Line Below 100 Percent ...... 9.8 2.8 2.1 4.4 0.5 11.6 100 to 150 Percent ...... 5.1 1.4 1.1 2.3 Q 14.2 Above 150 ...

  5. char_household2001.pdf

    Annual Energy Outlook [U.S. Energy Information Administration (EIA)]

    Income Relative to Poverty Line Below 100 Percent ...... 5.2 3.9 Q Q 1.1 21.9 100 to 150 Percent ...... 6.4 5.2 0.2 Q 0.9 16.5 Above 150 Percent ...

  6. char_household2001.pdf

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Income Relative to Poverty Line Below 100 Percent ...... 15.0 6.7 2.3 ... 4.9 Q Q 0.2 14.8 1 Below 150 percent of poverty line or 60 percent of median State ...

  7. EPA Webinar- Solar for All: Making it Happen in Low-Income Communities

    Broader source: Energy.gov [DOE]

    Hosted by the U.S. Environmental Protection Agency (EPA), this webinar is the third in a multi-part series highlighting efforts by state and local agencies, nonprofits, and utilities to bring energy efficiency and renewable energy to low-income households.

  8. appl_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    0a. Appliances by Midwest Census Region, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total U.S. Midwest Census Region RSE Row Factors Total Census Division East North Central West North Central 0.5 1.0 1.2 1.5 Total .............................................................. 107.0 24.5 17.1 7.4 NE Kitchen Appliances Cooking Appliances Oven ......................................................... 101.7 23.8 16.6 7.2 NE 1

  9. appl_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    1a. Appliances by South Census Region, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total U.S. South Census Region RSE Row Factors Total Census Division South Atlantic East South Central West South Central 0.5 0.8 1.1 1.4 1.5 Total .............................................................. 107.0 38.9 20.3 6.8 11.8 NE Kitchen Appliances Cooking Appliances Oven ......................................................... 101.7 36.2 19.4 6.4 10.3 1.5 1

  10. appl_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    4a. Appliances by Type of Housing Unit, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total Type of Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.4 0.5 1.7 1.6 1.9 Total ............................................... 107.0 73.7 9.5 17.0 6.8 4.2 Kitchen Appliances Cooking Appliances Oven ........................................... 101.7 69.1 9.4 16.7 6.6 4.3 1

  11. appl_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    5a. Appliances by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total Owner- Occupied Units Type of Owner-Occupied Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.3 0.4 2.1 3.1 1.3 Total ............................................... 72.7 63.2 2.1 1.8 5.7 6.7 Kitchen Appliances Cooking Appliances Oven ...........................................

  12. appl_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    6a. Appliances by Type of Rented Housing Unit, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total Rented Units Type of Rented Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.5 0.8 1.1 0.9 2.5 Total ............................................... 34.3 10.5 7.4 15.2 1.1 6.9 Kitchen Appliances Cooking Appliances Oven ........................................... 33.4 10.1 7.3 14.9 1.1

  13. appl_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    8a. Appliances by Urban/Rural Location, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total Urban/Rural Location 1 RSE Row Factors City Town Suburbs Rural 0.5 0.9 1.4 1.2 1.3 Total .............................................................. 107.0 49.9 18.0 21.2 17.9 4.1 Kitchen Appliances Cooking Appliances Oven ......................................................... 101.7 47.5 17.5 19.9 16.8 4.2 1

  14. appl_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    9a. Appliances by Northeast Census Region, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.0 1.3 1.6 Total .............................................................. 107.0 20.3 14.8 5.4 NE Kitchen Appliances Cooking Appliances Oven ......................................................... 101.7 19.6 14.5 5.2 1.1 1

  15. homeoffice_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    2001 Home Office Equipment RSE Column Factor: Total U.S. Four Most Populated States RSE Row Factors New York California Texas Florida 0.4 1.1 1.0 1.5 1.5 Total .............................................................. 107.0 7.1 12.3 7.7 6.3 NE Households Using Office Equipment ......................................... 96.2 6.2 11.4 6.7 5.9 1.7 Personal Computers 1 ................................. 60.0 3.4 7.9 4.1 3.8 4.4 Number of Desktop PCs 1

  16. spaceheat_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    0a. Space Heating by Midwest Census Region, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total U.S. Midwest Census Region RSE Row Factors Total Census Division East North Central West North Central 0.5 1.0 1.2 1.6 Total .............................................................. 107.0 24.5 17.1 7.4 NE Heat Home .................................................... 106.0 24.5 17.1 7.4 NE Do Not Heat Home ....................................... 1.0 Q Q Q 19.8 No

  17. spaceheat_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    1a. Space Heating by South Census Region, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total U.S. South Census Region RSE Row Factors Total Census Division South Atlantic East South Central West South Central 0.5 0.9 1.2 1.4 1.3 Total .............................................................. 107.0 38.9 20.3 6.8 11.8 NE Heat Home .................................................... 106.0 38.8 20.2 6.8 11.8 NE Do Not Heat Home

  18. spaceheat_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    2a. Space Heating by West Census Region, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total Census Division Mountain Pacific 0.6 1.0 1.6 1.2 Total .............................................................. 107.0 23.3 6.7 16.6 NE Heat Home .................................................... 106.0 22.6 6.7 15.9 NE Do Not Heat Home ....................................... 1.0 0.7 Q 0.7 10.6 No Heating Equipment

  19. spaceheat_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    5a. Space Heating by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total Owner- Occupied Units Type of Owner-Occupied Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.4 0.4 1.9 3.0 1.3 Total ............................................... 72.7 63.2 2.1 1.8 5.7 6.7 Heat Home ..................................... 72.4 63.0 2.0 1.7 5.7 6.7 Do Not Heat Home

  20. spaceheat_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    6a. Space Heating by Type of Rented Housing Unit, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total Rented Units Type of Rented Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.5 0.8 1.1 0.9 2.5 Total ............................................... 34.3 10.5 7.4 15.2 1.1 6.9 Heat Home ..................................... 33.7 10.4 7.4 14.8 1.1 6.9 Do Not Heat Home

  1. spaceheat_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    8a. Space Heating by Urban/Rural Location, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total Urban/Rural Location 1 RSE Row Factors City Town Suburbs Rural 0.6 0.9 1.3 1.3 1.2 Total .............................................................. 107.0 49.9 18.0 21.2 17.9 4.3 Heat Home .................................................... 106.0 49.1 18.0 21.2 17.8 4.3 Do Not Heat Home ....................................... 1.0 0.7 0.1 0.1 0.1 25.8 No Heating

  2. spaceheat_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    9a. Space Heating by Northeast Census Region, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.0 1.2 1.7 Total .............................................................. 107.0 20.3 14.8 5.4 NE Heat Home .................................................... 106.0 20.1 14.7 5.4 NE Do Not Heat Home ....................................... 1.0 Q Q Q 19.9 No

  3. Comparison of energy expenditures by elderly and non-elderly households: 1975 and 1985

    SciTech Connect (OSTI)

    Siler, A.

    1980-05-01

    The relative position of the elderly in the population is examined and their characteristic use of energy in relation to the total population and their non-elderly counterparts is observed. The 1985 projections are based on demographic, economic, and socio-economic, and energy data assumptions contained in the 1978 Annual Report to Congress. The model used for estimating household energy expenditure is MATH/CHRDS - Micro-Analysis of Transfers to Households/Comprehensive Human Resources Data System. Characteristics used include households disposable income, poverty status, location by DOE region and Standard Metropolitan Statistical Area (SMSA), and race and sex of the household head as well as age. Energy use by fuel type will be identified for total home fuels, including electricity, natural gas, bottled gas and fuel oil, and for all fuels, where gasoline use is also included. Throughout the analysis, both income and expenditure-dollar amounts for 1975 and 1985 are expressed in constant 1978 dollars. Two appendices contain statistical information.

  4. Nebraska Natural Gas Gross Withdrawals and Production

    U.S. Energy Information Administration (EIA) Indexed Site

    09 2010 2011 2012 2013 2014 View History Gross Withdrawals 2,916 2,255 1,980 1,328 1,032 402 1967-2014 From Gas Wells 2,734 2,092 1,854 1,317 1,027 400 1967-2014 From Oil Wells 182 163 126 11 5 1 1967-2014 From Shale Gas Wells 0 0 0 0 0 0 2007-2014 From Coalbed Wells 0 0 0 0 0 0 2006-2014 Repressuring 0 0 0 0 0 0 1967-2014 Vented and Flared 9 24 21 0 NA NA 1967-2014 Nonhydrocarbon Gases Removed 0 0 0 0 0 0 2006-2014 Marketed Production 2,908 2,231 1,959 1,328 1,032 402 1967-2014 Dry Production

  5. Pennsylvania Natural Gas Gross Withdrawals and Production

    U.S. Energy Information Administration (EIA) Indexed Site

    10 2011 2012 2013 2014 2015 View History Gross Withdrawals 572,902 1,310,592 2,256,696 3,259,042 4,214,643 4,768,848 1967-2015 From Gas Wells 173,450 242,305 210,609 207,872 174,576 1967-2014 From Oil Wells 0 0 3,456 2,987 3,564 1967-2014 From Shale Gas Wells 399,452 1,068,288 2,042,632 3,048,182 4,036,504 2007-2014 From Coalbed Wells 0 0 0 0 0 2006-2014 Repressuring 0 0 0 0 0 1967-2014 Vented and Flared 0 0 0 0 0 1967-2014 Nonhydrocarbon Gases Removed 0 0 0 0 0 1997-2014 Marketed Production

  6. Virginia Natural Gas Gross Withdrawals and Production

    U.S. Energy Information Administration (EIA) Indexed Site

    09 2010 2011 2012 2013 2014 View History Gross Withdrawals 140,738 147,255 151,094 146,405 139,382 131,885 1967-2014 From Gas Wells 16,046 23,086 20,375 21,802 26,815 27,052 1967-2014 From Oil Wells 0 0 0 9 9 9 2006-2014 From Shale Gas Wells 18,284 16,433 18,501 17,212 13,016 12,226 2007-2014 From Coalbed Wells 106,408 107,736 112,219 107,383 99,542 92,599 2006-2014 Repressuring 0 0 0 0 0 0 2003-2014 Vented and Flared NA NA NA 0 NA NA 1967-2014 Nonhydrocarbon Gases Removed 0 0 0 0 0 0 1997-2014

  7. Kansas Natural Gas Gross Withdrawals and Production

    U.S. Energy Information Administration (EIA) Indexed Site

    10 2011 2012 2013 2014 2015 View History Gross Withdrawals 325,591 309,952 296,299 292,467 286,080 292,450 1967-2015 From Gas Wells 247,651 236,834 264,610 264,223 260,715 1967-2014 From Oil Wells 39,071 37,194 0 0 0 1967-2014 From Shale Gas Wells 0 0 0 0 0 2007-2014 From Coalbed Wells 38,869 35,924 31,689 28,244 25,365 2002-2014 Repressuring 548 521 0 NA NA 1967-2014 Vented and Flared 323 307 0 NA NA 1967-2014 Nonhydrocarbon Gases Removed 0 0 0 0 0 2002-2014 Marketed Production 324,720 309,124

  8. Kentucky Natural Gas Gross Withdrawals and Production

    U.S. Energy Information Administration (EIA) Indexed Site

    09 2010 2011 2012 2013 2014 View History Gross Withdrawals 113,300 135,330 124,243 106,122 94,665 78,737 1967-2014 From Gas Wells 111,782 133,521 122,578 106,122 94,665 78,737 1967-2014 From Oil Wells 1,518 1,809 1,665 0 0 0 1967-2014 From Shale Gas Wells 0 0 0 0 0 0 2007-2014 From Coalbed Wells 0 0 0 0 0 0 2006-2014 Repressuring 0 0 0 0 0 0 2006-2014 Vented and Flared 0 0 0 0 0 0 1967-2014 Nonhydrocarbon Gases Removed 0 0 0 0 0 0 2006-2014 Marketed Production 113,300 135,330 124,243 106,122

  9. Louisiana Natural Gas Gross Withdrawals and Production

    U.S. Energy Information Administration (EIA) Indexed Site

    10 2011 2012 2013 2014 2015 View History Gross Withdrawals 2,218,283 3,040,523 2,955,437 2,366,943 1,987,630 1,941,727 1967-2015 From Gas Wells 911,967 883,712 775,506 780,623 737,185 1967-2014 From Oil Wells 63,638 68,505 49,380 51,948 50,638 1967-2014 From Shale Gas Wells 1,242,678 2,088,306 2,130,551 1,534,372 1,199,807 2007-2014 From Coalbed Wells 0 0 0 0 0 2002-2014 Repressuring 3,606 5,015 0 2,829 3,199 1967-2014 Vented and Flared 4,578 6,302 0 3,912 4,143 1967-2014 Nonhydrocarbon Gases

  10. ,"Federal Offshore Gulf of Mexico Natural Gas Gross Withdrawals...

    U.S. Energy Information Administration (EIA) Indexed Site

    Gulf of Mexico Natural Gas Gross Withdrawals and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest...

  11. ,"New Mexico Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","New Mexico Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  12. ,"West Virginia Natural Gas Gross Withdrawals from Shale Gas...

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ... Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","1...

  13. ,"Tennessee Natural Gas Gross Withdrawals from Shale Gas (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ... Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","1...

  14. ,"Missouri Natural Gas Gross Withdrawals from Shale Gas (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ... Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","1...

  15. ,"Louisiana Natural Gas Gross Withdrawals from Shale Gas (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ... Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","1...

  16. ,"Wyoming Natural Gas Gross Withdrawals from Shale Gas (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ... Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","1...

  17. ,"Michigan Natural Gas Gross Withdrawals from Shale Gas (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ... Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","1...

  18. ,"Mississippi Natural Gas Gross Withdrawals from Shale Gas (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ... Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","1...

  19. ,"Virginia Natural Gas Gross Withdrawals from Shale Gas (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ... Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","1...

  20. ,"Oregon Natural Gas Gross Withdrawals from Shale Gas (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ... Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","1...

  1. ,"Oklahoma Natural Gas Gross Withdrawals from Shale Gas (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ... Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","1...

  2. ,"Utah Natural Gas Gross Withdrawals from Shale Gas (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ... Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","1...

  3. ,"Ohio Natural Gas Gross Withdrawals from Shale Gas (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ... Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","1...

  4. ,"Montana Natural Gas Gross Withdrawals from Shale Gas (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ... Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","1...

  5. ,"South Dakota Natural Gas Gross Withdrawals from Shale Gas ...

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ... Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","1...

  6. Gross Gamma-Ray Calibration Blocks (May 1978) | Department of...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    for, and the Procedures Currently Utilized in, Gross Gamma-Ray Log Calibration (October 1976) Parameter Assignments for Spectral Gamma-Ray Borehole Calibration Models (April 1984

  7. ,"West Virginia Natural Gas Gross Withdrawals and Production...

    U.S. Energy Information Administration (EIA) Indexed Site

    Of Series","Frequency","Latest Data for" ,"Data 1","West Virginia Natural Gas Gross Withdrawals and Production",10,"Monthly","22016","1151991" ,"Release ...

  8. ,"Other States Total Natural Gas Gross Withdrawals and Production...

    U.S. Energy Information Administration (EIA) Indexed Site

    Total Natural Gas Gross Withdrawals and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ...

  9. ,"New Mexico Natural Gas Gross Withdrawals from Oil Wells (MMcf...

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","New Mexico Natural Gas Gross Withdrawals from Oil Wells (MMcf)",1,"Annual",2014 ,"Release...

  10. ,"New Mexico Natural Gas Gross Withdrawals from Gas Wells (MMcf...

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","New Mexico Natural Gas Gross Withdrawals from Gas Wells (MMcf)",1,"Annual",2014 ,"Release...

  11. Household energy consumption and expenditures, 1990

    SciTech Connect (OSTI)

    Not Available

    1993-03-02

    This report, Household Energy Consumption and Expenditures 1990, is based upon data from the 1990 Residential Energy Consumption Survey (RECS). Focusing on energy end-use consumption and expenditures of households, the 1990 RECS is the eighth in a series conducted since 1978 by the Energy Information Administration (EIA). Over 5,000 households were surveyed, providing information on their housing units, housing characteristics, energy consumption and expenditures, stock of energy-consuming appliances, and energy-related behavior. The information provided represents the characteristics and energy consumption of 94 million households nationwide.

  12. appl_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    a. Appliances by Climate Zone, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total Climate Zone 1 RSE Row Factors Fewer than 2,000 CDD and -- 2,000 CDD or More and Fewer than 4,000 HDD More than 7,000 HDD 5,500 to 7,000 HDD 4,000 to 5,499 HDD Fewer than 4,000 HDD 0.4 1.9 1.1 1.1 1.2 1.1 Total .................................................. 107.0 9.2 28.6 24.0 21.0 24.1 7.8 Kitchen Appliances Cooking Appliances Oven

  13. appl_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    2a. Appliances by Year of Construction, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total Year of Construction RSE Row Factors 1990 to 2001 1 1980 to 1989 1970 to 1979 1960 to 1969 1950 to 1959 1949 or Before 0.4 1.5 1.2 1.1 1.2 1.1 0.9 Total ............................................... 107.0 15.5 18.2 18.8 13.8 14.2 26.6 4.2 Kitchen Appliances Cooking Appliances Oven ........................................... 101.7 14.3 17.2 17.8 12.9 13.7 25.9 4.2 1

  14. spaceheat_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    2a. Space Heating by Year of Construction, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total Year of Construction RSE Row Factors 1990 to 2001 1 1980 to 1989 1970 to 1979 1960 to 1969 1950 to 1959 1949 or Before 0.5 1.5 1.1 1.1 1.1 1.1 0.9 Total ............................................... 107.0 15.5 18.2 18.8 13.8 14.2 26.6 4.3 Heat Home ..................................... 106.0 15.4 18.2 18.6 13.6 13.9 26.4 4.3 Do Not Heat Home ........................

  15. spaceheat_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    4a. Space Heating by Type of Housing Unit, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total Type of Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.5 0.5 1.5 1.4 1.7 Total ............................................... 107.0 73.7 9.5 17.0 6.8 4.4 Heat Home ..................................... 106.0 73.4 9.4 16.4 6.8 4.5 Do Not Heat Home ........................ 1.0 0.3 Q 0.6 Q 19.0 No

  16. ASSESSMENT OF HOUSEHOLD CARBON FOOTPRINT REDUCTION POTENTIALS

    SciTech Connect (OSTI)

    Kramer, Klaas Jan; Homan, Greg; Brown, Rich; Worrell, Ernst; Masanet, Eric

    2009-04-15

    The term ?household carbon footprint? refers to the total annual carbon emissions associated with household consumption of energy, goods, and services. In this project, Lawrence Berkeley National Laboratory developed a carbon footprint modeling framework that characterizes the key underlying technologies and processes that contribute to household carbon footprints in California and the United States. The approach breaks down the carbon footprint by 35 different household fuel end uses and 32 different supply chain fuel end uses. This level of end use detail allows energy and policy analysts to better understand the underlying technologies and processes contributing to the carbon footprint of California households. The modeling framework was applied to estimate the annual home energy and supply chain carbon footprints of a prototypical California household. A preliminary assessment of parameter uncertainty associated with key model input data was also conducted. To illustrate the policy-relevance of this modeling framework, a case study was conducted that analyzed the achievable carbon footprint reductions associated with the adoption of energy efficient household and supply chain technologies.

  17. Kingston Creek Hydro Project Powers 100 Households | Department...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Kingston Creek Hydro Project Powers 100 Households Kingston Creek Hydro Project Powers 100 Households August 21, 2013 - 12:00am Addthis Nevada-based contracting firm Nevada ...

  18. Energy Information Administration/Household Vehicles Energy Consumptio...

    U.S. Energy Information Administration (EIA) Indexed Site

    , Energy Information AdministrationHousehold Vehicles Energy Consumption 1994 ix Household Vehicles Energy Consumption 1994 presents statistics about energy-related...

  19. Household Response To Dynamic Pricing Of Electricity: A Survey...

    Open Energy Info (EERE)

    Household Response To Dynamic Pricing Of Electricity: A Survey Of The Experimental Evidence Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Household Response To Dynamic...

  20. Microsoft Word - Household Energy Use CA

    Gasoline and Diesel Fuel Update (EIA)

    0 20 40 60 80 100 US PAC CA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US PAC CA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US PAC CA Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US PAC CA Expenditures dollars ELECTRICITY ONLY average per household  California households use 62 million Btu of energy per home, 31% less than the U.S. average. The lower than average site

  1. Microsoft Word - Household Energy Use CA

    U.S. Energy Information Administration (EIA) Indexed Site

    0 20 40 60 80 100 US PAC CA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US PAC CA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US PAC CA Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US PAC CA Expenditures dollars ELECTRICITY ONLY average per household  California households use 62 million Btu of energy per home, 31% less than the U.S. average. The lower than average site

  2. South Dakota Natural Gas Gross Withdrawals from Coalbed Wells (Million

    U.S. Energy Information Administration (EIA) Indexed Site

    Cubic Feet) Coalbed Wells (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 0 0 0 0 2010's 0 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 8/31/2016 Next Release Date: 9/30/2016 Referring Pages: Natural Gas Gross Withdrawals from Coalbed Wells South Dakota Natural Gas Gross Withdrawals and Production Natural Gas Gross Withdrawals from

  3. Household energy consumption and expenditures 1993

    SciTech Connect (OSTI)

    1995-10-05

    This presents information about household end-use consumption of energy and expenditures for that energy. These data were collected in the 1993 Residential Energy Consumption Survey; more than 7,000 households were surveyed for information on their housing units, energy consumption and expenditures, stock of energy-consuming appliances, and energy-related behavior. The information represents all households nationwide (97 million). Key findings: National residential energy consumption was 10.0 quadrillion Btu in 1993, a 9% increase over 1990. Weather has a significant effect on energy consumption. Consumption of electricity for appliances is increasing. Houses that use electricity for space heating have lower overall energy expenditures than households that heat with other fuels. RECS collected data for the 4 most populous states: CA, FL, NY, TX.

  4. Other States Natural Gas Gross Withdrawals from Gas Wells (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Gas Wells (Million Cubic Feet) Other States Natural Gas Gross Withdrawals from Gas Wells (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1991 72,328 ...

  5. Other States Natural Gas Gross Withdrawals from Coalbed Wells...

    U.S. Energy Information Administration (EIA) Indexed Site

    Coalbed Wells (Million Cubic Feet) Other States Natural Gas Gross Withdrawals from Coalbed Wells (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2002 0 0 ...

  6. Other States Natural Gas Gross Withdrawals from Oil Wells (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Oil Wells (Million Cubic Feet) Other States Natural Gas Gross Withdrawals from Oil Wells (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1991 3,459 3,117 ...

  7. Missouri Natural Gas Gross Withdrawals from Oil Wells (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    from Oil Wells (Million Cubic Feet) Missouri Natural Gas Gross Withdrawals from Oil Wells (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 ...

  8. Physics Nobel winner David Gross gives public lecture at Jefferson...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Nobel winner David Gross gives public lecture at Jefferson Lab on June 12 (Monday) Physics ... "The Coming Revolutions in Fundamental Physics" beginning at 8 p.m. at Jefferson Lab on ...

  9. Fact #564: March 30, 2009 Transportation and the Gross Domestic...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Housing, health care, and food are the only categories with greater shares of the GDP. GDP ... Gross Domestic Product, 2007 Housing 24.3% Health Care 17.4% Food 11.6% ...

  10. Montana Natural Gas Gross Withdrawals from Gas Wells (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Gas Wells (Million Cubic Feet) Montana Natural Gas Gross Withdrawals from Gas Wells (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1991 4,561 3,826 4,106 ...

  11. Utah Natural Gas Gross Withdrawals from Gas Wells (Million Cubic...

    U.S. Energy Information Administration (EIA) Indexed Site

    Gas Wells (Million Cubic Feet) Utah Natural Gas Gross Withdrawals from Gas Wells (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1991 21,638 18,808 21,037 ...

  12. Oklahoma Natural Gas Gross Withdrawals from Shale Gas (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet) Oklahoma Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2007 7,051 6,368 ...

  13. Louisiana Natural Gas Gross Withdrawals from Gas Wells (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Gas Wells (Million Cubic Feet) Louisiana Natural Gas Gross Withdrawals from Gas Wells (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1991 425,704 369,500 ...

  14. Florida Natural Gas Gross Withdrawals from Gas Wells (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Gas Wells (Million Cubic Feet) Florida Natural Gas Gross Withdrawals from Gas Wells (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1996 - - - - - - - - - ...

  15. Ohio Natural Gas Gross Withdrawals from Shale Gas (Million Cubic...

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet) Ohio Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2007 1 1 1 1 1 1 1 1 1 1 ...

  16. Michigan Natural Gas Gross Withdrawals from Gas Wells (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Gas Wells (Million Cubic Feet) Michigan Natural Gas Gross Withdrawals from Gas Wells (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1991 9,579 8,593 ...

  17. Montana Natural Gas Gross Withdrawals from Shale Gas (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet) Montana Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2007 1,239 1,119 1,239 ...

  18. Michigan Natural Gas Gross Withdrawals from Shale Gas (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet) Michigan Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2007 11,582 10,461 ...

  19. Virginia Natural Gas Gross Withdrawals from Shale Gas (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet) Virginia Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2007 1,622 1,465 ...

  20. Louisiana Natural Gas Gross Withdrawals from Shale Gas (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet) Louisiana Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2007 1,273 1,150 ...

  1. Oregon Natural Gas Gross Withdrawals from Gas Wells (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    from Gas Wells (Million Cubic Feet) Oregon Natural Gas Gross Withdrawals from Gas Wells (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1991 246 244 232 ...

  2. Colorado Natural Gas Gross Withdrawals from Shale Gas (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet) Colorado Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2007 11,749 10,612 ...

  3. Mississippi Natural Gas Gross Withdrawals from Gas Wells (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Gas Wells (Million Cubic Feet) Mississippi Natural Gas Gross Withdrawals from Gas Wells (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1991 14,797 13,076 ...

  4. Wyoming Natural Gas Gross Withdrawals from Gas Wells (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Gas Wells (Million Cubic Feet) Wyoming Natural Gas Gross Withdrawals from Gas Wells (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1991 58,111 51,244 ...

  5. Utah Natural Gas Gross Withdrawals from Shale Gas (Million Cubic...

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet) Utah Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2007 0 0 0 0 0 0 0 0 0 0 ...

  6. Wyoming Natural Gas Gross Withdrawals from Shale Gas (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet) Wyoming Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2007 331 299 331 320 ...

  7. Colorado Natural Gas Gross Withdrawals from Gas Wells (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Gas Wells (Million Cubic Feet) Colorado Natural Gas Gross Withdrawals from Gas Wells (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1991 15,390 18,697 ...

  8. Pennsylvania Natural Gas Gross Withdrawals from Shale Gas (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    from Shale Gas (Million Cubic Feet) Pennsylvania Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2007 0 0 0 0 ...

  9. Texas Natural Gas Gross Withdrawals from Shale Gas (Million Cubic...

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet) Texas Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2007 107,415 97,020 ...

  10. Federal Offshore--Gulf of Mexico Natural Gas Gross Withdrawals...

    U.S. Energy Information Administration (EIA) Indexed Site

    Gas Wells (Million Cubic Feet) Federal Offshore--Gulf of Mexico Natural Gas Gross Withdrawals from Gas Wells (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov ...

  11. Fact# 904: December 21, 2015 Gross Domestic Product and Vehicle...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    With the growth of VMT in 2015, the gap between the two series has narrowed for the first time since the Great Recession. GDP and VMT Trends, 1960-2015 Graph showing gross national ...

  12. Property:CoolingTowerWaterUseSummerGross | Open Energy Information

    Open Energy Info (EERE)

    Property Name CoolingTowerWaterUseSummerGross Property Type Number Description Cooling Tower Water use (summer average) (afday) Gross. Retrieved from "http:en.openei.orgw...

  13. A Multi Agent-Based Framework for Simulating Household PHEV Distribution and Electric Distribution Network Impact

    SciTech Connect (OSTI)

    Cui, Xiaohui; Liu, Cheng; Kim, Hoe Kyoung; Kao, Shih-Chieh; Tuttle, Mark A; Bhaduri, Budhendra L

    2011-01-01

    The variation of household attributes such as income, travel distance, age, household member, and education for different residential areas may generate different market penetration rates for plug-in hybrid electric vehicle (PHEV). Residential areas with higher PHEV ownership could increase peak electric demand locally and require utilities to upgrade the electric distribution infrastructure even though the capacity of the regional power grid is under-utilized. Estimating the future PHEV ownership distribution at the residential household level can help us understand the impact of PHEV fleet on power line congestion, transformer overload and other unforeseen problems at the local residential distribution network level. It can also help utilities manage the timing of recharging demand to maximize load factors and utilization of existing distribution resources. This paper presents a multi agent-based simulation framework for 1) modeling spatial distribution of PHEV ownership at local residential household level, 2) discovering PHEV hot zones where PHEV ownership may quickly increase in the near future, and 3) estimating the impacts of the increasing PHEV ownership on the local electric distribution network with different charging strategies. In this paper, we use Knox County, TN as a case study to show the simulation results of the agent-based model (ABM) framework. However, the framework can be easily applied to other local areas in the US.

  14. Material World: Forecasting Household Appliance Ownership in a Growing Global Economy

    SciTech Connect (OSTI)

    Letschert, Virginie; McNeil, Michael A.

    2009-03-23

    Over the past years the Lawrence Berkeley National Laboratory (LBNL) has developed an econometric model that predicts appliance ownership at the household level based on macroeconomic variables such as household income (corrected for purchase power parity), electrification, urbanization and climate variables. Hundreds of data points from around the world were collected in order to understand trends in acquisition of new appliances by households, especially in developing countries. The appliances covered by this model are refrigerators, lighting fixtures, air conditioners, washing machines and televisions. The approach followed allows the modeler to construct a bottom-up analysis based at the end use and the household level. It captures the appliance uptake and the saturation effect which will affect the energy demand growth in the residential sector. With this approach, the modeler can also account for stock changes in technology and efficiency as a function of time. This serves two important functions with regard to evaluation of the impact of energy efficiency policies. First, it provides insight into which end uses will be responsible for the largest share of demand growth, and therefore should be policy priorities. Second, it provides a characterization of the rate at which policies affecting new equipment penetrate the appliance stock. Over the past 3 years, this method has been used to support the development of energy demand forecasts at the country, region or global level.

  15. WPN 00-3- 2000 Poverty Income Guidelines and Definition of Income

    Broader source: Energy.gov [DOE]

    To provide states with the 2000 Poverty Income Guidelines and Definition of Income for use in the low-income Weatherization Assistance Program.

  16. WPN 14-3: 2014 Poverty Income Guidance and Definition of Income

    Office of Energy Efficiency and Renewable Energy (EERE)

    To provide Grantees with the 2014 Poverty Income Guidelines and Definition of Income for use in the Low-Income Weatherization Assistance Program (WAP).

  17. WPN 03-3: 2003 Poverty Income Guidelines and Definition of Income

    Office of Energy Efficiency and Renewable Energy (EERE)

    To provide states with the 2003 Poverty Income Guidelines and Definition of Income for use in the low-income Weatherization Assistance Program.

  18. WPN 06-5: Poverty Income Guidelines and Definition of Income

    Office of Energy Efficiency and Renewable Energy (EERE)

    To provide states with the 2006 Poverty Income Guidelines and Definition of Income for use in the low-income Weatherization Assistance Program.

  19. WPN 07-3: Poverty Income Guidelines and Definition of Income

    Office of Energy Efficiency and Renewable Energy (EERE)

    To provide states with the 2007 poverty income guidelines and definition of income for use in the low-income Weatherization Assistance Program.

  20. WPN 13-3: 2013 Poverty Income Guidelines and Definition of Income

    Office of Energy Efficiency and Renewable Energy (EERE)

    To provide states with the 2013 Poverty Income Guidelines and Definition of Income for use in the low-income Weatherization Assistance Program (WAP).

  1. WPN 98-5- 1998 Poverty Income Guidelines and Definition of Income

    Office of Energy Efficiency and Renewable Energy (EERE)

    To provide states with the 1998 Poverty Income Guidelines and Definition of Income for use in the low-income Weatherization Assistance Program.

  2. WPN 04-5: 2004 Poverty Income Guidelines and Definition of Income

    Office of Energy Efficiency and Renewable Energy (EERE)

    To provide states with the 2004 Poverty Income Guidelines and Definition of Income for use in the low-income Weatherization Assistance Program.

  3. WPN 02-3: 2002 Poverty Income Guidelines and Definition of Income

    Broader source: Energy.gov [DOE]

    To provide states with the 2002 Poverty Income Guidelines and Definition of Income for use in the low-income Weatherization Assistance Program.

  4. Low-income energy assistance programs: a profile of need and policy options

    SciTech Connect (OSTI)

    None

    1980-07-01

    This second report of the Fuel Oil Marketing Advisory Committee (FOMAC) of DOE is twofold: to update information on the energy needs of low-income persons and governmental response to such needs; and to emphasize the need for energy-conservation programs that may alleviate the enormous financial burden placed on low-income people by rising energy prices. FOMAC has continued to develop further and refine its initial energy-conservation recommendations. Mainly, the updated assessment document finds that the poor will expend at least 35% of their income directly on energy and will spend at least 21% of their income on household energy. Other economic impacts of rising energy costs on low-income groups are summarized. Appropriations and stipulations by Congress to aid the lo-income people are reviewed. After careful review of various program designs, FOMAC continues to support the income indexing/vendor line of credit approach. This design provides assistance to elgible households based on: energy needed, cost of fuel, and percentage of income. The cost of implementing the FOMAC design nationally would, according to estimates, range from $3.5 to $4.6 billion for the 1980-1981 winter heating season. A figure of $1.6 to $2.2 billion is being discussed in the Congress. Meeting the ongoing energy needs of the poor will require a coherent national policy which consists of aid in paying energy bills and aid in the poor's effort to conserve energy. The report seeks to promote such policies. Needs assessment, government response, FOMAC model, comments on the programs, projected cost of 1980-1981 Energy Assistance Program, need for conservation programs, and program financing are discussed.

  5. The impact of forecasted energy price increases on low-income consumers

    SciTech Connect (OSTI)

    Eisenberg, Joel F.

    2005-10-31

    The Department of Energy’s Energy Information Administration (EIA) recently released its short term forecast for residential energy prices for the winter of 2005-2006. The forecast indicates significant increases in fuel costs, particularly for natural gas, propane, and home heating oil, for the year ahead. In the following analysis, the Oak Ridge National Laboratory has integrated the EIA price projections with the Residential Energy Consumption Survey (RECS) for 2001 in order to project the impact of these price increases on the nation’s low-income households by primary heating fuel type, nationally and by Census Region. The statistics are intended for the use of policymakers in the Department of Energy’s Weatherization Assistance Program and elsewhere who are trying to gauge the nature and severity of the problems that will be faced by eligible low-income households during the 2006 fiscal year.

  6. Gross alpha analytical modifications that improve wastewater treatment compliance

    SciTech Connect (OSTI)

    Tucker, B.J.; Arndt, S.

    2007-07-01

    This paper will propose an improvement to the gross alpha measurement that will provide more accurate gross alpha determinations and thus allow for more efficient and cost-effective treatment of site wastewaters. To evaluate the influence of salts that may be present in wastewater samples from a potentially broad range of environmental conditions, two types of efficiency curves were developed, each using a thorium-230 (Th-230) standard spike. Two different aqueous salt solutions were evaluated, one using sodium chloride, and one using salts from tap water drawn from the Bergen County, New Jersey Publicly Owned Treatment Works (POTW). For each curve, 13 to 17 solutions were prepared, each with the same concentration of Th-230 spike, but differing in the total amount of salt in the range of 0 to 100 mg. The attenuation coefficients were evaluated for the two salt types by plotting the natural log of the counted efficiencies vs. the weight of the sample's dried residue retained on the planchet. The results show that the range of the slopes for each of the attenuation curves varied by approximately a factor of 2.5. In order to better ensure the accuracy of results, and thus verify compliance with the gross alpha wastewater effluent criterion, projects depending on gross alpha measurements of environmental waters and wastewaters should employ gross alpha efficiency curves prepared with salts that mimic, as closely as possible, the salt content of the aqueous environmental matrix. (authors)

  7. Mitigating Carbon Emissions: the Potential of Improving Efficiencyof Household Appliances in China

    SciTech Connect (OSTI)

    Lin, Jiang

    2006-07-10

    China is already the second's largest energy consumer in the world after the United States, and its demand for energy is expected to continue to grow rapidly in the foreseeable future, due to its fast economic growth and its low level of energy use per capita. From 2001 to 2005, the growth rate of energy consumption in China has exceeded the growth rate of its economy (NBS, 2006), raising serious concerns about the consequences of such energy use on local environment and global climate. It is widely expected that China is likely to overtake the US in energy consumption and greenhouse gas (GHG) emissions during the first half of the 21st century. Therefore, there is considerable interest in the international community in searching for options that may help China slow down its growth in energy consumption and GHG emissions through improving energy efficiency and adopting more environmentally friendly fuel supplies such as renewable energy. This study examines the energy saving potential of three major residential energy end uses: household refrigeration, air-conditioning, and water heating. China is already the largest consumer market in the world for household appliances, and increasingly the global production base for consumer appliances. Sales of household refrigerators, room air-conditioners, and water heaters are growing rapidly due to rising incomes and booming housing market. At the same time, the energy use of Chinese appliances is relatively inefficient compared to similar products in the developed economies. Therefore, the potential for energy savings through improving appliance efficiency is substantial. This study focuses particularly on the impact of more stringent energy efficiency standards for household appliances, given that such policies are found to be very effective in improving the efficiency of household appliances, and are well established both in China and around world (CLASP, 2006).

  8. Messaging Strategies for Low-Income Participants

    Broader source: Energy.gov [DOE]

    Better Buildings Neighborhood Program, BetterBuildings Low-Income Peer Exchange Call: Messaging and Messaging Strategies for Low-Income Program Participants, May 12, 2011.

  9. WPN 15-3: 2015 Poverty Income Guidelines and Definition of Income |

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Department of Energy 3: 2015 Poverty Income Guidelines and Definition of Income WPN 15-3: 2015 Poverty Income Guidelines and Definition of Income Archived 02/10/16, Superseded by WPN 16-3 To provide Grantees with the 2015 Poverty Income Guidelines and Definition of Income for use in the low-income Weatherization Assistance Program (WAP). WPN 15-3: 2015 Poverty Income Guidelines and Definition of Income (293.58 KB) More Documents & Publications WPN 14-3: 2014 Poverty Income Guidance and

  10. Federal Offshore Louisiana Natural Gas Gross Withdrawals and...

    U.S. Energy Information Administration (EIA) Indexed Site

    Data Series Area 2009 2010 2011 2012 2013 2014 View History Gross Withdrawals NA NA NA 0 0 0 1977-2014 From Gas Wells NA NA NA 0 0 0 1977-2014 From Oil Wells NA NA NA 0 0 0 ...

  11. Kansas Natural Gas Gross Withdrawals from Shale Gas (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2007 0 0 0 0 0 0 0 0 0 0 0 0 2008 0 0 0 0 0 0 0 0 0 0 0 0 ...

  12. Mississippi Natural Gas Gross Withdrawals from Shale Gas (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Mississippi Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2007 0 0 0 0 0 0 0 0 0 0 0 0 2008 0 0 0 0 0 0 0 0 ...

  13. Nebraska Natural Gas Gross Withdrawals from Shale Gas (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2007 0 0 0 0 0 0 0 0 0 0 0 0 2008 0 0 0 0 0 0 0 0 0 0 0 0 ...

  14. New Mexico Natural Gas Gross Withdrawals and Production

    U.S. Energy Information Administration (EIA) Indexed Site

    Gross Withdrawals 1,341,475 1,287,682 1,276,296 1,247,394 1,265,579 1,289,908 1967-2015 From Gas Wells 616,134 556,024 653,057 588,127 535,181 1967-2014 From Oil Wells 238,580 ...

  15. Low-Income Weatherization: The Human Dimension

    Office of Energy Efficiency and Renewable Energy (EERE)

    This presentation focuses on how the human dimension saves energy within low-income weatherization programs.

  16. Determinants of Household Use of Selected Energy Star Appliances - Energy

    Gasoline and Diesel Fuel Update (EIA)

    Information Administration Determinants of Household Use of Selected Energy Star Appliances Release date: May 25, 2016 Introduction According to the 2009 Residential Energy Consumption Survey (RECS), household appliances1accounted for 35% of U.S. household energy consumption, up from 24% in 1993. Thus, improvements in the energy performance of residential appliances as well as increases in the use of more efficient appliances can be effective in reducing household energy consumption and

  17. Left to Our Own Devices – Financing Efficiency for Small Business and Low-Income Families (2009 Environmental Defense Fund Report)

    Office of Energy Efficiency and Renewable Energy (EERE)

    There is a widely known gap between cost-effective behavior, consumption patterns and actual marketplace conditions. This engineering gap/efficiency gap is particularly the case for low-income households and small businesses, which tend to depend on older, inefficient equipment. This study identifies the limitations of current and potential of relatively new mechanisms for efficiency investment micro-financing.

  18. Household Energy Consumption Segmentation Using Hourly Data

    SciTech Connect (OSTI)

    Kwac, J; Flora, J; Rajagopal, R

    2014-01-01

    The increasing US deployment of residential advanced metering infrastructure (AMI) has made hourly energy consumption data widely available. Using CA smart meter data, we investigate a household electricity segmentation methodology that uses an encoding system with a pre-processed load shape dictionary. Structured approaches using features derived from the encoded data drive five sample program and policy relevant energy lifestyle segmentation strategies. We also ensure that the methodologies developed scale to large data sets.

  19. Household energy consumption and expenditures, 1987

    SciTech Connect (OSTI)

    Not Available

    1989-10-10

    Household Energy Consumption and Expenditures 1987, Part 1: National Data is the second publication in a series from the 1987 Residential Energy Consumption Survey (RECS). It is prepared by the Energy End Use Division (EEUD) of the Office of Energy Markets and End Use (EMEU), Energy Information Administration (EIA). The EIA collects and publishes comprehensive data on energy consumption in occupied housing units in the residential sector through the RECS. 15 figs., 50 tabs.

  20. Alabama Natural Gas Gross Withdrawals Total Offshore (Million Cubic Feet)

    U.S. Energy Information Administration (EIA) Indexed Site

    Gross Withdrawals Total Offshore (Million Cubic Feet) Alabama Natural Gas Gross Withdrawals Total Offshore (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 0 9 13 1990's 19,861 32,603 191,605 218,023 349,380 356,598 361,068 409,091 392,320 376,435 2000's 361,289 200,862 202,002 194,339 165,630 152,902 145,762 134,451 125,502 109,214 2010's 101,487 84,270 87,398 75,660 70,827 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  1. Alabama--onshore Natural Gas Gross Withdrawals (Million Cubic Feet)

    U.S. Energy Information Administration (EIA) Indexed Site

    Gross Withdrawals (Million Cubic Feet) Alabama--onshore Natural Gas Gross Withdrawals (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 222,009 228,298 229,483 223,527 221,233 220,674 212,470 207,863 2000's 200,255 191,119 184,500 176,571 173,106 164,304 160,381 155,167 152,051 146,751 2010's 139,215 134,305 128,312 120,666 110,226 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  2. Alaska Natural Gas Gross Withdrawals Total Offshore (Million Cubic Feet)

    U.S. Energy Information Administration (EIA) Indexed Site

    Gross Withdrawals Total Offshore (Million Cubic Feet) Alaska Natural Gas Gross Withdrawals Total Offshore (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 72,813 71,946 1980's 63,355 71,477 66,852 68,776 68,315 62,454 63,007 69,656 101,440 122,595 1990's 144,064 171,665 216,377 233,198 224,301 113,552 126,051 123,854 133,111 125,841 2000's 263,958 262,937 293,580 322,010 334,125 380,568 354,816 374,204 388,188 357,490 2010's 370,148 364,702

  3. Alaska--onshore Natural Gas Gross Withdrawals (Million Cubic Feet)

    U.S. Energy Information Administration (EIA) Indexed Site

    Gross Withdrawals (Million Cubic Feet) Alaska--onshore Natural Gas Gross Withdrawals (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 2,409,336 2,545,144 2,861,599 3,256,352 3,247,533 3,257,096 3,245,736 3,236,241 2000's 3,265,436 3,164,843 3,183,857 3,256,295 3,309,960 3,262,379 2,850,934 3,105,086 3,027,696 2,954,896 2010's 2,826,952 2,798,220 2,857,485 2,882,956 2,803,429 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  4. Calif--onshore Natural Gas Gross Withdrawals (Million Cubic Feet)

    U.S. Energy Information Administration (EIA) Indexed Site

    Gross Withdrawals (Million Cubic Feet) Calif--onshore Natural Gas Gross Withdrawals (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 386,382 346,733 334,987 322,544 326,919 317,137 315,701 347,667 2000's 334,983 336,629 322,138 303,480 287,205 291,271 301,921 286,584 281,088 258,983 2010's 273,136 237,388 214,509 219,386 218,512 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  5. California Natural Gas Gross Withdrawals Total Offshore (Million Cubic

    U.S. Energy Information Administration (EIA) Indexed Site

    Feet) Gross Withdrawals Total Offshore (Million Cubic Feet) California Natural Gas Gross Withdrawals Total Offshore (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 5,417 19,929 20,394 1980's 19,980 26,692 31,904 38,084 60,207 84,062 77,355 67,835 60,308 59,889 1990's 58,055 59,465 62,473 58,635 60,765 60,694 73,092 80,516 81,868 84,547 2000's 83,882 78,209 74,884 64,961 61,622 60,773 47,217 52,805 51,931 47,281 2010's 46,755 41,742

  6. Federal Offshore California Natural Gas Gross Withdrawals (Million Cubic

    U.S. Energy Information Administration (EIA) Indexed Site

    Feet) Gross Withdrawals (Million Cubic Feet) Federal Offshore California Natural Gas Gross Withdrawals (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 5,417 5,166 5,431 1980's 5,900 12,763 17,751 24,168 46,363 64,558 59,078 54,805 49,167 50,791 1990's 49,972 51,855 55,231 52,150 53,561 54,790 66,784 73,345 74,985 77,809 2000's 76,075 70,947 67,816 58,095 54,655 54,088 40,407 45,516 44,902 41,229 2010's 41,200 36,579 27,262 27,454

  7. Texas Natural Gas Gross Withdrawals Total Offshore (Million Cubic Feet)

    U.S. Energy Information Administration (EIA) Indexed Site

    Gross Withdrawals Total Offshore (Million Cubic Feet) Texas Natural Gas Gross Withdrawals Total Offshore (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 88,258 418,474 760,566 1980's 949,177 1,010,772 1,120,830 992,041 1,021,260 942,413 1,169,038 1,330,604 1,376,093 1,457,841 1990's 1,555,568 1,494,494 1,411,147 1,355,333 1,392,727 1,346,674 1,401,753 1,351,067 1,241,264 1,206,045 2000's 1,177,257 53,649 57,063 53,569 44,946 36,932 24,785

  8. Texas--onshore Natural Gas Gross Withdrawals (Million Cubic Feet)

    U.S. Energy Information Administration (EIA) Indexed Site

    Gross Withdrawals (Million Cubic Feet) Texas--onshore Natural Gas Gross Withdrawals (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 5,296,865 5,461,594 5,518,978 5,525,982 5,626,448 5,665,074 5,738,595 5,526,033 2000's 5,681,726 5,698,798 5,603,941 5,737,755 5,688,972 5,969,905 6,301,649 6,931,629 7,753,869 7,615,836 2010's 7,565,123 7,910,898 8,127,004 8,285,436 8,652,111 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  9. Louisiana Natural Gas Gross Withdrawals Total Offshore (Million Cubic Feet)

    U.S. Energy Information Administration (EIA) Indexed Site

    Gross Withdrawals Total Offshore (Million Cubic Feet) Louisiana Natural Gas Gross Withdrawals Total Offshore (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 3,838,521 4,600,197 4,750,119 1980's 4,617,585 4,584,491 4,246,464 3,635,942 4,070,279 3,542,827 3,279,165 3,610,041 3,633,594 3,577,685 1990's 3,731,764 3,550,230 3,442,437 3,508,112 3,673,494 3,554,147 3,881,697 3,941,802 3,951,997 3,896,569 2000's 3,812,991 153,871 137,192 133,456

  10. Louisiana--onshore Natural Gas Gross Withdrawals (Million Cubic Feet)

    U.S. Energy Information Administration (EIA) Indexed Site

    Gross Withdrawals (Million Cubic Feet) Louisiana--onshore Natural Gas Gross Withdrawals (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 1,535,033 1,538,511 1,552,603 1,608,633 1,469,698 1,357,155 1,386,478 1,434,389 2000's 1,342,963 1,370,802 1,245,270 1,244,672 1,248,050 1,202,328 1,280,758 1,309,960 1,301,523 1,482,252 2010's 2,148,447 2,969,297 2,882,193 2,289,193 1,925,968 - = No Data Reported; -- = Not Applicable; NA = Not Available;

  11. Property:CoolingTowerWaterUseWinterGross | Open Energy Information

    Open Energy Info (EERE)

    lingTowerWaterUseWinterGross Property Type Number Description Cooling Tower Water use (winter average) (afday) Gross. Retrieved from "http:en.openei.orgwindex.php?titleProper...

  12. Property:CoolingTowerWaterUseAnnlAvgGross | Open Energy Information

    Open Energy Info (EERE)

    Property Name CoolingTowerWaterUseAnnlAvgGross Property Type Number Description Cooling Tower Water use (annual average) (afday) Gross. Retrieved from "http:en.openei.orgw...

  13. Household and environmental characteristics related to household energy-consumption change: A human ecological approach

    SciTech Connect (OSTI)

    Guerin, D.A.

    1988-01-01

    This study focused on the family household as an organism and on its interaction with the three environments of the human ecosystem (natural, behavioral, and constructed) as these influence energy consumption and energy-consumption change. A secondary statistical analysis of data from the US Department of Energy Residential Energy Consumption Surveys (RECS) was completed. The 1980 and 1983 RECS were used as the data base. Longitudinal data, including household, environmental, and energy-consumption measures, were available for over 800 households. The households were selected from a national sample of owner-occupied housing units surveyed in both years. Results showed a significant( p = <.05) relationship between the dependent-variable energy-consumption change and the predictor variables heating degree days, addition of insulation, addition of a wood-burning stove, year the housing unit was built, and weighted number of appliances. A significant (p = <.05) relationship was found between the criterion variable energy-consumption change and the discriminating variables of age of the head of the household, cooling degree days, heating degree days, year the housing unit was built, and number of stories in the housing unit.

  14. Physics Nobel winner David Gross gives public lecture at Jefferson Lab on

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    June 12 (Monday) | Jefferson Lab Nobel winner David Gross gives public lecture at Jefferson Lab on June 12 (Monday) Physics Nobel winner David Gross gives public lecture at Jefferson Lab on June 12 (Monday) June 6, 2006 David Gross David Gross, Nobel Prize recipient and lecturer David Gross, Nobel Prize recipient is scheduled to give a free, public lecture titled "The Coming Revolutions in Fundamental Physics" beginning at 8 p.m. at Jefferson Lab on (Monday) June 12. He is one of

  15. Messaging Strategies for Low-Income Participants | Department...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Messaging Strategies for Low-Income Participants Messaging Strategies for Low-Income Participants Better Buildings Neighborhood Program, BetterBuildings Low-Income Peer Exchange ...

  16. Strategies for Collecting Household Energy Data | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Collecting Household Energy Data Strategies for Collecting Household Energy Data Better Buildings Neighborhood Program Data and Evaluation Peer Exchange Call: Strategies for Collecting Household Energy Data, Call Slides and Discussion Summary, July 19, 2012. Call Slides and Discussion Summary (700.06 KB) More Documents & Publications Homeowner and Contractor Surveys Mastermind: Jim Mikel, Spirit Foundation Generating Energy Efficiency Project Leads and Allocating Leads to Contractors

  17. Gross Input to Atmospheric Crude Oil Distillation Units

    U.S. Energy Information Administration (EIA) Indexed Site

    Day) Process: Gross Input to Atmospheric Crude Oil Dist. Units Operable Capacity (Calendar Day) Operating Capacity Idle Operable Capacity Operable Utilization Rate Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Process Area Jan-16 Feb-16 Mar-16 Apr-16 May-16 Jun-16 View History U.S. 16,365 16,167 16,261 16,222 16,477 16,803 1985-2016 PADD 1 1,136 1,080 1,052 1,148 1,174 1,155 1985-2016 East

  18. WPN 05-4a- 2005 Poverty Income Guidelines and Definition of Income to Exclude Combat Zone Pay

    Broader source: Energy.gov [DOE]

    To provide states with the 2005 Poverty Income Guidelines and Definition of Income for use in the low-income Weatherization Assistance Program.

  19. Household energy consumption and expenditures 1987

    SciTech Connect (OSTI)

    Not Available

    1990-01-22

    This report is the third in the series of reports presenting data from the 1987 Residential Energy Consumption Survey (RECS). The 1987 RECS, seventh in a series of national surveys of households and their energy suppliers, provides baseline information on household energy use in the United States. Data from the seven RECS and its companion survey, the Residential Transportation Energy Consumption Survey (RTECS), are made available to the public in published reports such as this one, and on public use data files. This report presents data for the four Census regions and nine Census divisions on the consumption of and expenditures for electricity, natural gas, fuel oil and kerosene (as a single category), and liquefied petroleum gas (LPG). Data are also presented on consumption of wood at the Census region level. The emphasis in this report is on graphic depiction of the data. Data from previous RECS surveys are provided in the graphics, which indicate the regional trends in consumption, expenditures, and uses of energy. These graphs present data for the United States and each Census division. 12 figs., 71 tabs.

  20. Appliance Commitment for Household Load Scheduling

    SciTech Connect (OSTI)

    Du, Pengwei; Lu, Ning

    2011-06-30

    This paper presents a novel appliance commitment algorithm that schedules thermostatically-controlled household loads based on price and consumption forecasts considering users comfort settings to meet an optimization objective such as minimum payment or maximum comfort. The formulation of an appliance commitment problem was described in the paper using an electrical water heater load as an example. The thermal dynamics of heating and coasting of the water heater load was modeled by physical models; random hot water consumption was modeled with statistical methods. The models were used to predict the appliance operation over the scheduling time horizon. User comfort was transformed to a set of linear constraints. Then, a novel linear, sequential, optimization process was used to solve the appliance commitment problem. The simulation results demonstrate that the algorithm is fast, robust, and flexible. The algorithm can be used in home/building energy-management systems to help household owners or building managers to automatically create optimal load operation schedules based on different cost and comfort settings and compare cost/benefits among schedules.

  1. Household energy consumption and expenditures, 1990. [Contains Glossary

    SciTech Connect (OSTI)

    Not Available

    1993-03-02

    This report, Household Energy Consumption and Expenditures 1990, is based upon data from the 1990 Residential Energy Consumption Survey (RECS). Focusing on energy end-use consumption and expenditures of households, the 1990 RECS is the eighth in a series conducted since 1978 by the Energy Information Administration (EIA). Over 5,000 households were surveyed, providing information on their housing units, housing characteristics, energy consumption and expenditures, stock of energy-consuming appliances, and energy-related behavior. The information provided represents the characteristics and energy consumption of 94 million households nationwide.

  2. Barriers to household investment in residential energy conservation: preliminary assessment

    SciTech Connect (OSTI)

    Hoffman, W.L.

    1982-12-01

    A general assessment of the range of barriers which impede household investments in weatherization and other energy efficiency improvements for their homes is provided. The relationship of similar factors to households' interest in receiving a free energy audits examined. Rates of return that underly household investments in major conservation improvements are assessed. A special analysis of household knowledge of economically attractive investments is provided that compares high payback improvements specified by the energy audit with the list of needed or desirable conservation improvements identified by respondents. (LEW)

  3. California--State Offshore Natural Gas Gross Withdrawals (Million Cubic

    U.S. Energy Information Administration (EIA) Indexed Site

    Feet) Gross Withdrawals (Million Cubic Feet) California--State Offshore Natural Gas Gross Withdrawals (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 14,763 14,963 1980's 14,080 13,929 14,153 13,916 13,844 19,504 18,277 13,030 11,141 9,098 1990's 8,083 7,610 7,242 6,484 7,204 5,904 6,309 7,171 6,883 6,738 2000's 7,808 7,262 7,068 6,866 6,966 6,685 6,809 7,289 7,029 6,052 2010's 5,554 5,163 5,051 5,470 5,961 - = No Data Reported; -- =

  4. An Analysis of the Price Elasticity of Demand for Household Appliances

    SciTech Connect (OSTI)

    Fujita, Kimberly; Dale, Larry; Fujita, K. Sydny

    2008-01-25

    This report summarizes our study of the price elasticity of demand for home appliances, including refrigerators, clothes washers, and dishwashers. In the context of increasingly stringent appliance standards, we are interested in what kind of impact the increased manufacturing costs caused by higher efficiency requirements will have on appliance sales. We begin with a review of existing economics literature describing the impact of economic variables on the sale of durable goods.We then describe the market for home appliances and changes in this market over the past 20 years, performing regression analysis on the shipments of home appliances and relevant economic variables including changes to operating cost and household income. Based on our analysis, we conclude that the demand for home appliances is price inelastic.

  5. Upgrade energy building standards and develop rating system for existing low-income housing

    SciTech Connect (OSTI)

    Muller, D.; Norville, C.

    1993-07-01

    The city of Memphis Division of Housing and Community Development (HCD) receives grant funding each year from the U.S. Department of Housing and Urban Development (HUD) to provide local housing assistance to low-income residents. Through the years, HCD has found that many of the program recipients have had difficulty in managing their households, particularly in meeting monthly financial obligations. One of the major operating costs to low-income households is the utility bill. Furthermore, HCD`s experience has revealed that many low-income residents are simply unaware of ways to reduce their utility bill. Most of the HCD funds are distributed to low-income persons as grants or no/low interest loans for the construction or rehabilitation of single-family dwellings. With these funds, HCD builds 80 to 100 new houses and renovates about 500 homes each year. Houses constructed or renovated by HCD must meet HUD`s minimum energy efficiency standards. While these minimum standards are more than adequate to meet local building codes, they are not as aggressive as the energy efficiency standards being promoted by the national utility organizations and the home building industry. Memphis Light, Gas and Water (MLGW), a city-owned utility, has developed an award-winning program named Comfort Plus which promotes energy efficiency{open_quote} in new residential construction. Under Comfort Plus, MLGW models house plans on computer for a fee and recommends cost-effective alterations which improve the energy efficiency of the house. If the builder agrees to include these recommendations, MLGW will certify the house and guarantee a maximum annual heating/cooling bill for two years. While the Comfort Plus program has received recognition in the new construction market, it does not address the existing housing stock.

  6. Table 6.4 Natural Gas Gross Withdrawals and Natural Gas Well Productivity, 1960-2011

    U.S. Energy Information Administration (EIA) Indexed Site

    Natural Gas Gross Withdrawals and Natural Gas Well Productivity, 1960-2011 Year Natural Gas Gross Withdrawals From Crude Oil, Natural Gas, Coalbed, and Shale Gas Wells Natural Gas Well Productivity Texas 1 Louisiana 1 Oklahoma Other States 1 Federal Gulf of Mexico 2 Total Onshore Offshore Total Gross With- drawals From Natural Gas Wells 3 Producing Wells 4 Average Productivity Federal State Total Million Cubic Feet Million Cubic Feet Million Cubic Feet Number Cubic Feet per Well 1960 6,964,900

  7. Fact# 904: December 21, 2015 Gross Domestic Product and Vehicle Travel:

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Both Increased during 2015 | Department of Energy 4: December 21, 2015 Gross Domestic Product and Vehicle Travel: Both Increased during 2015 Fact# 904: December 21, 2015 Gross Domestic Product and Vehicle Travel: Both Increased during 2015 SUBSCRIBE to the Fact of the Week The nation's highway vehicle miles of travel (VMT) and the U.S. gross domestic product (GDP) reflect strikingly similar patterns, indicating the strong relationship between the nation's economy and its travel. Beginning in

  8. Fact #904: December 21, 2015 Gross Domestic Product and Vehicle Travel:

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Both Increased during 2015 - Dataset | Department of Energy Fact #904: December 21, 2015 Gross Domestic Product and Vehicle Travel: Both Increased during 2015 - Dataset Fact #904: December 21, 2015 Gross Domestic Product and Vehicle Travel: Both Increased during 2015 - Dataset Excel file and dataset for Gross Domestic Product and Vehicle Travel: Both Increased during 2015 fotw#904_web_rev.xlsx (19.75 KB) More Documents & Publications Vehicle Technologies Office Spring 2016 Quarterly

  9. Other States Total Natural Gas Gross Withdrawals and Production

    U.S. Energy Information Administration (EIA) Indexed Site

    Monthly-Million Cubic Feet Monthly-Million Cubic Feet per Day Annual-Million Cubic Feet Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Data Series Area 2010 2011 2012 2013 2014 2015 View History Gross Withdrawals 5,864,402 6,958,125 8,225,321 689,082 633,853 596,357 1991-2015 From Gas Wells 2,523,173 2,599,172 3,177,021 362,605 328,809 1991-2014 From Oil Wells 691,643 728,857 279,627 23,391 22,817 1991-2014 From

  10. Gross national happiness as a framework for health impact assessment

    SciTech Connect (OSTI)

    Pennock, Michael; Ura, Karma

    2011-01-15

    The incorporation of population health concepts and health determinants into Health Impact Assessments has created a number of challenges. The need for intersectoral collaboration has increased; the meaning of 'health' has become less clear; and the distinctions between health impacts, environmental impacts, social impacts and economic impacts have become increasingly blurred. The Bhutanese concept of Gross National Happiness may address these issues by providing an over-arching evidence-based framework which incorporates health, social, environmental and economic contributors as well as a number of other key contributors to wellbeing such as culture and governance. It has the potential to foster intersectoral collaboration by incorporating a more limited definition of health which places the health sector as one of a number of contributors to wellbeing. It also allows for the examination of the opportunity costs of health investments on wellbeing, is consistent with whole-of-government approaches to public policy and emerging models of social progress.

  11. Oregon Natural Gas Gross Withdrawals from Coalbed Wells (Million Cubic

    Gasoline and Diesel Fuel Update (EIA)

    Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 24,171 52,846 49,661 2000's 69,451 82,542 55,854 74,400 88,734 87,998 75,186 101,503 116,637 108,705 2010's 108,827 60,252 81,444 101,930 90,099 113

    09 2010 2011 2012 2013 2014 View History Gross Withdrawals 821 1,407 1,344 770 770 950 1979-2014 From Gas Wells 821 1,407 1,344 770 770 950 1979-2014 From Oil Wells 0 0 0 0 0 0 1996-2014 From Shale Gas Wells 0 0 0 0 0 0 2007-2014 From Coalbed Wells 0 0 0

  12. Pennsylvania Natural Gas Gross Withdrawals from Coalbed Wells (Million

    Gasoline and Diesel Fuel Update (EIA)

    Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 20,430 30,240 31,353 2000's 20,597 22,632 50,251 41,238 76,186 80,640 100,946 143,954 141,011 210,542 2010's 245,559 306,266 393,775 362,349 390,816 439,248

    10 2011 2012 2013 2014 2015 View History Gross Withdrawals 572,902 1,310,592 2,256,696 3,259,042 4,214,643 4,768,848 1967-2015 From Gas Wells 173,450 242,305 210,609 207,872 174,576 1967-2014 From Oil Wells 0 0 3,456 2,987 3,564 1967-2014

  13. Fact #564: March 30, 2009 Transportation and the Gross Domestic Product,

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    2007 | Department of Energy 4: March 30, 2009 Transportation and the Gross Domestic Product, 2007 Fact #564: March 30, 2009 Transportation and the Gross Domestic Product, 2007 Transportation plays a major role in the U.S. economy. About 10% of the U.S. Gross Domestic Product (GDP) in 2007 is related to transportation. Housing, health care, and food are the only categories with greater shares of the GDP. GDP by Category, 2007 Graph showing the Gross Domestic Product (GDP) for various

  14. Spatial confinement and thermal deconfinement in the Gross-Neveu model

    SciTech Connect (OSTI)

    Malbouisson, J. M. C.; Khanna, F. C.; Malbouisson, A. P. C.

    2007-06-19

    We discuss the occurrence of spatial confinement and thermal deconfinement in the massive, D-dimensional, Gross-Neveu model with compactified spatial dimensions.

  15. Low Income Home Energy Assistance Program (LIHEAP)

    Broader source: Energy.gov [DOE]

    The Low Income Home Energy Assistance Program (LIHEAP) provides resources to assist families with energy costs. This federally funded assistance helps in managing costs associated with:

  16. Low Income Energy Efficiency Workgroup Meeting #1

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    for a session at the Efficiency Exchange conference in April and is looking for winning strategies for acquiring low income energy efficiency. The first session focused on...

  17. WPN 12-8: 2012 Poverty Income Guidelines and Definition of Income

    Office of Energy Efficiency and Renewable Energy (EERE)

    To provide Grantees with the 2012 Poverty Income Guidelines and Definition of Income for use in the U.S. Department of Energy’s (DOE) Weatherization Assistance Program (WAP).

  18. Reconstructing householder vectors from Tall-Skinny QR

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Ballard, Grey Malone; Demmel, James; Grigori, Laura; Jacquelin, Mathias; Knight, Nicholas; Nguyen, Hong Diep

    2015-08-05

    The Tall-Skinny QR (TSQR) algorithm is more communication efficient than the standard Householder algorithm for QR decomposition of matrices with many more rows than columns. However, TSQR produces a different representation of the orthogonal factor and therefore requires more software development to support the new representation. Further, implicitly applying the orthogonal factor to the trailing matrix in the context of factoring a square matrix is more complicated and costly than with the Householder representation. We show how to perform TSQR and then reconstruct the Householder vector representation with the same asymptotic communication efficiency and little extra computational cost. We demonstratemore » the high performance and numerical stability of this algorithm both theoretically and empirically. The new Householder reconstruction algorithm allows us to design more efficient parallel QR algorithms, with significantly lower latency cost compared to Householder QR and lower bandwidth and latency costs compared with Communication-Avoiding QR (CAQR) algorithm. Experiments on supercomputers demonstrate the benefits of the communication cost improvements: in particular, our experiments show substantial improvements over tuned library implementations for tall-and-skinny matrices. Furthermore, we also provide algorithmic improvements to the Householder QR and CAQR algorithms, and we investigate several alternatives to the Householder reconstruction algorithm that sacrifice guarantees on numerical stability in some cases in order to obtain higher performance.« less

  19. Reconstructing householder vectors from Tall-Skinny QR

    SciTech Connect (OSTI)

    Ballard, Grey Malone; Demmel, James; Grigori, Laura; Jacquelin, Mathias; Knight, Nicholas; Nguyen, Hong Diep

    2015-08-05

    The Tall-Skinny QR (TSQR) algorithm is more communication efficient than the standard Householder algorithm for QR decomposition of matrices with many more rows than columns. However, TSQR produces a different representation of the orthogonal factor and therefore requires more software development to support the new representation. Further, implicitly applying the orthogonal factor to the trailing matrix in the context of factoring a square matrix is more complicated and costly than with the Householder representation. We show how to perform TSQR and then reconstruct the Householder vector representation with the same asymptotic communication efficiency and little extra computational cost. We demonstrate the high performance and numerical stability of this algorithm both theoretically and empirically. The new Householder reconstruction algorithm allows us to design more efficient parallel QR algorithms, with significantly lower latency cost compared to Householder QR and lower bandwidth and latency costs compared with Communication-Avoiding QR (CAQR) algorithm. Experiments on supercomputers demonstrate the benefits of the communication cost improvements: in particular, our experiments show substantial improvements over tuned library implementations for tall-and-skinny matrices. Furthermore, we also provide algorithmic improvements to the Householder QR and CAQR algorithms, and we investigate several alternatives to the Householder reconstruction algorithm that sacrifice guarantees on numerical stability in some cases in order to obtain higher performance.

  20. Perceptions of risk among households in two Australian coastal communities

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Elrick-Barr, Carmen E.; Smith, Timothy F.; Thomsen, Dana C.; Preston, Benjamin L.

    2015-04-20

    There is limited knowledge of risk perceptions in coastal communities despite their vulnerability to a range of risks including the impacts of climate change. A survey of 400 households in two Australian coastal communities, combined with semi-structured interviews, provides insight into household perceptions of the relative importance of climatic and non-climatic risks and the subsequent risk priorities that may inform household adaptive action. In contrast to previous research, the results demonstrated that geographic location and household characteristics might not affect perceptions of vulnerability to environmental hazards. However, past experience was a significant influence, raising the priority of environmental concerns. Overall,more » the results highlight the priority concerns of coastal households (from finance, to health and environment) and suggest to increase the profile of climate issues in coastal communities climate change strategies need to better demonstrate links between climate vulnerability and other household concerns. Moreover, promoting generic capacities in isolation from understanding the context in which households construe climate risks is unlikely to yield the changes required to decrease the vulnerability of coastal communities.« less

  1. Perceptions of risk among households in two Australian coastal communities

    SciTech Connect (OSTI)

    Elrick-Barr, Carmen E.; Smith, Timothy F.; Thomsen, Dana C.; Preston, Benjamin L.

    2015-04-20

    There is limited knowledge of risk perceptions in coastal communities despite their vulnerability to a range of risks including the impacts of climate change. A survey of 400 households in two Australian coastal communities, combined with semi-structured interviews, provides insight into household perceptions of the relative importance of climatic and non-climatic risks and the subsequent risk priorities that may inform household adaptive action. In contrast to previous research, the results demonstrated that geographic location and household characteristics might not affect perceptions of vulnerability to environmental hazards. However, past experience was a significant influence, raising the priority of environmental concerns. Overall, the results highlight the priority concerns of coastal households (from finance, to health and environment) and suggest to increase the profile of climate issues in coastal communities climate change strategies need to better demonstrate links between climate vulnerability and other household concerns. Moreover, promoting generic capacities in isolation from understanding the context in which households construe climate risks is unlikely to yield the changes required to decrease the vulnerability of coastal communities.

  2. Fact #618: April 12, 2010 Vehicles per Household and Other Demographic...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    per Household and Other Demographic Statistics Fact 618: April 12, 2010 Vehicles per Household and Other Demographic Statistics Since 1969, the number of vehicles per ...

  3. Buildings Energy Data Book: 2.9 Low-Income Housing

    Buildings Energy Data Book [EERE]

    9 2005 Housing Unit Ownership, by Income Level and Weatherization Eligibility (Millions) Single-Family Multi-Family Unit Mobile Home 2005 Household Income Own Rent Own Rent Own Rent Less than $15,000 6.1 2.4 0.3 7.1 1.6 N.A. $15,000 to $30,000 11.0 3.0 0.4 5.8 2.2 0.3 $30,000 to $49,999 15.7 2.5 N.A 3.9 1.2 N.A. All Households 68.2 10.7 4.2 20.1 5.7 1.0 Federally Eligible 10.9 4.5 1.1 9.4 2.5 0.6 Federally Ineligible 57.3 6.2 3.1 10.7 3.2 0.4 Below 100% Poverty Line 5.3 2.4 0.7 6.1 1.5 0.3

  4. Measuring Income and Projecting Energy Use

    SciTech Connect (OSTI)

    Pitcher, Hugh M.

    2009-11-01

    Abstract: Energy is a key requirement for a healthy, productive life and a major driver of the emissions leading to an increasingly warm planet. The implications of a doubling and redoubling of per capita incomes over the remainder of this century for energy use are a critical input into understanding the magnitude of the carbon management problem. A substantial controversy about how the Special Report on Emssions Scenarios (SRES) measured income and the potential implications of how income was measured for long term levels of energy use is revisited again in the McKibbin, Pearce and Stegman article appearing elsewhere in this issue. The recent release of a new set of purchasing power estimates of national income, and the preparations for creating new scenarios to support the IPCCs fifth assessment highlight the importance of the issues which have arisen surrounding income and energy use. Comparing the 1993 and 2005 ICP results on Purchasing Power Parity (PPP) based measures of income reveals that not only do the 2005 ICP estimates share the same issue of common growth rates for real income as measured by PPP and US $, but the lack of coherence in the estimates of PPP incomes, especially for developing countries raises yet another obstacle to resolving the best way to measure income. Further, the common use of an income term to mediate energy demand (as in the Kaya identity) obscures an underlying reality about per capita energy demands, leading to unreasonable estimates of the impact of changing income measures and of the recent high GDP growth rates in India and China. Significant new research is required to create both a reasonable set of GDP growth rates and long term levels of energy use.

  5. Short and Long-Term Perspectives: The Impact on Low-Income Consumers of Forecasted Energy Price Increases in 2008 and A Cap & Trade Carbon Policy in 2030

    SciTech Connect (OSTI)

    Eisenberg, Joel Fred

    2008-01-01

    The Department of Energy's Energy Information Administration (EIA) recently released its short-term forecast for residential energy prices for the winter of 2007-2008. The forecast indicates increases in costs for low-income consumers in the year ahead, particularly for those using fuel oil to heat their homes. In the following analysis, the Oak Ridge National Laboratory has integrated the EIA price projections with the Residential Energy Consumption Survey (RECS) for 2001 in order to project the impact of these price increases on the nation's low-income households by primary heating fuel type, nationally and by Census Region. The report provides an update of bill estimates provided in a previous study, "The Impact Of Forecasted Energy Price Increases On Low-Income Consumers" (Eisenberg, 2005). The statistics are intended for use by policymakers in the Department of Energy's Weatherization Assistance Program and elsewhere who are trying to gauge the nature and severity of the problems that will be faced by eligible low-income households during the 2008 fiscal year. In addition to providing expenditure forecasts for the year immediately ahead, this analysis uses a similar methodology to give policy makers some insight into one of the major policy debates that will impact low-income energy expenditures well into the middle decades of this century and beyond. There is now considerable discussion of employing a cap-and-trade mechanism to first limit and then reduce U.S. emissions of carbon into the atmosphere in order to combat the long-range threat of human-induced climate change. The Energy Information Administration has provided an analysis of projected energy prices in the years 2020 and 2030 for one such cap-and-trade carbon reduction proposal that, when integrated with the RECS 2001 database, provides estimates of how low-income households will be impacted over the long term by such a carbon reduction policy.

  6. Fact #748: October 8, 2012 Components of Household Expenditures on

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Transportation, 1984-2010 | Department of Energy 8: October 8, 2012 Components of Household Expenditures on Transportation, 1984-2010 Fact #748: October 8, 2012 Components of Household Expenditures on Transportation, 1984-2010 The overall share of annual household expenditures for transportation was lower in 2010 than it was in 1984, reaching its lowest point in 2009 at 15.5%. In the early to mid-1980s when oil prices were high, gasoline and motor oil made up a larger share of transportation

  7. Table 2. Percent of Households with Vehicles, Selected Survey...

    U.S. Energy Information Administration (EIA) Indexed Site

    Percent of Households with Vehicles, Selected Survey Years " ,"Survey Years" ,1983,1985,1988,1991,1994,2001 "Total",85.5450237,89.00343643,88.75545852,89.42917548,87.25590956,92.08...

  8. Kentucky Natural Gas Gross Withdrawals from Coalbed Wells (Million Cubic

    Gasoline and Diesel Fuel Update (EIA)

    Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 2,194 5,782 5,686 2000's 4,202 4,433 13,712 3,667 4,833 17,181 12,287 19,376 9,584 8,399 2010's 19,284 15,575 31,194 14,536 26,919 52,015

    09 2010 2011 2012 2013 2014 View History Gross Withdrawals 113,300 135,330 124,243 106,122 94,665 78,737 1967-2014 From Gas Wells 111,782 133,521 122,578 106,122 94,665 78,737 1967-2014 From Oil Wells 1,518 1,809 1,665 0 0 0 1967-2014 From Shale Gas Wells 0 0 0 0 0

  9. Nebraska Natural Gas Gross Withdrawals from Coalbed Wells (Million Cubic

    Gasoline and Diesel Fuel Update (EIA)

    Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 2,687 5,080 4,582 2000's 5,522 4,290 4,947 4,593 3,340 8,066 7,787 10,908 7,230 3,331 2010's 3,949 4,223 7,696 5,080 4,132 4,634

    09 2010 2011 2012 2013 2014 View History Gross Withdrawals 2,916 2,255 1,980 1,328 1,032 402 1967-2014 From Gas Wells 2,734 2,092 1,854 1,317 1,027 400 1967-2014 From Oil Wells 182 163 126 11 5 1 1967-2014 From Shale Gas Wells 0 0 0 0 0 0 2007-2014 From Coalbed Wells 0 0 0

  10. Transferring 2001 National Household Travel Survey

    SciTech Connect (OSTI)

    Hu, Patricia S; Reuscher, Tim; Schmoyer, Richard L; Chin, Shih-Miao

    2007-05-01

    Policy makers rely on transportation statistics, including data on personal travel behavior, to formulate strategic transportation policies, and to improve the safety and efficiency of the U.S. transportation system. Data on personal travel trends are needed to examine the reliability, efficiency, capacity, and flexibility of the Nation's transportation system to meet current demands and to accommodate future demand. These data are also needed to assess the feasibility and efficiency of alternative congestion-mitigating technologies (e.g., high-speed rail, magnetically levitated trains, and intelligent vehicle and highway systems); to evaluate the merits of alternative transportation investment programs; and to assess the energy-use and air-quality impacts of various policies. To address these data needs, the U.S. Department of Transportation (USDOT) initiated an effort in 1969 to collect detailed data on personal travel. The 1969 survey was the first Nationwide Personal Transportation Survey (NPTS). The survey was conducted again in 1977, 1983, 1990, 1995, and 2001. Data on daily travel were collected in 1969, 1977, 1983, 1990 and 1995. In 2001, the survey was renamed the National Household Travel Survey (NHTS) and it collected both daily and long-distance trips. The 2001 survey was sponsored by three USDOT agencies: Federal Highway Administration (FHWA), Bureau of Transportation Statistics (BTS), and National Highway Traffic Safety Administration (NHTSA). The primary objective of the survey was to collect trip-based data on the nature and characteristics of personal travel so that the relationships between the characteristics of personal travel and the demographics of the traveler can be established. Commercial and institutional travel were not part of the survey. Due to the survey's design, data in the NHTS survey series were not recommended for estimating travel statistics for categories smaller than the combination of Census division (e.g., New England, Middle

  11. Ventilation Behavior and Household Characteristics in NewCalifornia Houses

    SciTech Connect (OSTI)

    Price, Phillip N.; Sherman, Max H.

    2006-02-01

    A survey was conducted to determine occupant use of windows and mechanical ventilation devices; barriers that inhibit their use; satisfaction with indoor air quality (IAQ); and the relationship between these factors. A questionnaire was mailed to a stratified random sample of 4,972 single-family detached homes built in 2003, and 1,448 responses were received. A convenience sample of 230 houses known to have mechanical ventilation systems resulted in another 67 completed interviews. Some results are: (1) Many houses are under-ventilated: depending on season, only 10-50% of houses meet the standard recommendation of 0.35 air changes per hour. (2) Local exhaust fans are under-utilized. For instance, about 30% of households rarely or never use their bathroom fan. (3) More than 95% of households report that indoor air quality is ''very'' or ''somewhat'' acceptable, although about 1/3 of households also report dustiness, dry air, or stagnant or humid air. (4) Except households where people cook several hours per week, there is no evidence that households with significant indoor pollutant sources get more ventilation. (5) Except households containing asthmatics, there is no evidence that health issues motivate ventilation behavior. (6) Security and energy saving are the two main reasons people close windows or keep them closed.

  12. Shared Renewable Energy for Low-to-Moderate Income Consumers...

    Office of Environmental Management (EM)

    Shared Renewable Energy for Low-to-Moderate Income Consumers: Policy Guidelines and Model Provisions Shared Renewable Energy for Low-to-Moderate Income Consumers: Policy Guidelines ...

  13. LIEE (LOW-INCOME ENERGY EFFICIENCY) GRANT PROGRAM VERSUS THE...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    614 LIEE (LOW-INCOME ENERGY EFFICIENCY) GRANT PROGRAM VERSUS THE UTILITY LOW-INCOME WEATHERIZATION & DUCT SEALING PROGRAM Program Requirements and Specifications Grant Program-...

  14. Proposed Structure and Organizing Principles for Low Income Energy...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Structure and Organizing Principles for Low Income Energy Efficiency Workgroup 1 Background As part of Post-2011-Review, BPA agreed to convene a low income energy efficiency...

  15. Better Buildings Low Income Peer Exchange CallFeaturing: Case...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    BetterBuildings Low Income Peer Exchange Call Featuring: Case study on integration of ... and Roll Call * Case study on integration of income-qualified programs into ...

  16. Effective Energy Behavior Change for Low-Income Weatherization...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Effective Energy Behavior Change for Low-Income Weatherization Clients Effective Energy Behavior Change for Low-Income Weatherization Clients This document contains the transcript ...

  17. Fact #618: April 12, 2010 Vehicles per Household and Other Demographic

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Statistics | Department of Energy 8: April 12, 2010 Vehicles per Household and Other Demographic Statistics Fact #618: April 12, 2010 Vehicles per Household and Other Demographic Statistics Since 1969, the number of vehicles per household has increased by 66% and the number of vehicles per licensed driver has increased by 47%. The number of workers per household has changed the least of the statistics shown here. There has been a decline in the number of persons per household from 1969 to

  18. Nevada Natural Gas Gross Withdrawals from Gas Wells (Million Cubic Feet)

    U.S. Energy Information Administration (EIA) Indexed Site

    from Gas Wells (Million Cubic Feet) Nevada Natural Gas Gross Withdrawals from Gas Wells (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 0 0 0 0 2010's 0 0 0 0 3 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 8/31/2016 Next Release Date: 9/30/2016 Referring Pages: Natural Gas Gross Withdrawals from Gas Wells Nevada Natural Gas Gross Withdrawals and

  19. Fact #621: May 3, 2010 Gross Vehicle Weight vs. Empty Vehicle Weight |

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Department of Energy 1: May 3, 2010 Gross Vehicle Weight vs. Empty Vehicle Weight Fact #621: May 3, 2010 Gross Vehicle Weight vs. Empty Vehicle Weight The gross weight of a vehicle (GVW) is the weight of the empty vehicle plus the weight of the maximum payload that the vehicle was designed to carry. In cars and small light trucks, the difference between the empty weight of the vehicle and the GVW is not significantly different (1,000 to 1,500 lbs). The largest trucks and tractor-trailers,

  20. Fact #768: February 25, 2013 New Light Vehicle Sales and Gross Domestic

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Product | Department of Energy 8: February 25, 2013 New Light Vehicle Sales and Gross Domestic Product Fact #768: February 25, 2013 New Light Vehicle Sales and Gross Domestic Product Over the last four decades, new light vehicle sales have gone from a low of 9.9 million vehicles in 1970 to a high of 17.1 million vehicles sold in 2001, but along the way, there have been significant ups and downs. Those ups and downs are also reflected in the change in Gross Domestic Product (GDP) over time

  1. The one-dimensional Gross-Pitaevskii equation and its some excitation states

    SciTech Connect (OSTI)

    Prayitno, T. B.

    2015-04-16

    We have derived some excitation states of the one-dimensional Gross-Pitaevskii equation coupled by the gravitational potential. The methods that we have used here are taken by pursuing the recent work of Kivshar et. al. by considering the equation as a macroscopic quantum oscillator. To obtain the states, we have made the appropriate transformation to reduce the three-dimensional Gross-Pitaevskii equation into the one-dimensional Gross-Pitaevskii equation and applying the time-independent perturbation theory in the general solution of the one-dimensional Gross-Pitaevskii equation as a linear superposition of the normalized eigenfunctions of the Schrödinger equation for the harmonic oscillator potential. Moreover, we also impose the condition by assuming that some terms in the equation should be so small in order to preserve the use of the perturbation method.

  2. ,"U.S. Natural Gas Gross Withdrawals from Shale Gas (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    2:54:05 AM" "Back to Contents","Data 1: U.S. Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)" "Sourcekey","NGMEPG0FGSNUSMMCF" "Date","U.S. Natural Gas ...

  3. EIA Energy Efficiency-Table 4e. Gross Output by Selected Industries...

    Annual Energy Outlook [U.S. Energy Information Administration (EIA)]

    e Page Last Modified: May 2010 Table 4e. Gross Output1by Selected Industries, 1998, 2002, and 2006 (Billion 2000 Dollars 2) MECS Survey Years NAICS Subsector and Industry 1998 2002...

  4. EIA Energy Efficiency-Table 3e. Gross Output by Selected Industries...

    Annual Energy Outlook [U.S. Energy Information Administration (EIA)]

    e Page Last Modified: May 2010 Table 3e. Gross Output1 by Selected Industries, 1998, 2002, and 2006 (Current Billion Dollars) MECS Survey Years NAICS Subsector and Industry 1998...

  5. OSTIblog Articles in the David Gross Topic | OSTI, US Dept of...

    Office of Scientific and Technical Information (OSTI)

    David Gross Topic 100th DOE R&D Accomplishments Feature Page Celebration by Linda McBrearty 07 Jul, 2013 in Products and Content 7566 Accomp100slide.preview.jpg 100th DOE R&D ...

  6. 23 V.S.A. Section 1392 Gross Weight Limits on Highways | Open...

    Open Energy Info (EERE)

    Section 1392 Gross Weight Limits on HighwaysLegal Abstract Statute establishes the motor vehicle weight, load size, not to exceed 80,000 pounds without a permit. Published NA...

  7. Modeling patterns of hot water use in households

    SciTech Connect (OSTI)

    Lutz, J.D.; Liu, Xiaomin; McMahon, J.E.

    1996-11-01

    This report presents a detailed model of hot water use patterns in individual household. The model improves upon an existing model by including the effects of four conditions that were previously unaccounted for: the absence of a clothes washer; the absence of a dishwasher; a household consisting of seniors only; and a household that does not pay for its own hot water use. Although these four conditions can significantly affect residential hot water use, and have been noted in other studies, this is the first time that they have been incorporated into a detailed model. This model allows detailed evaluation of the impact of potential efficiency standards for water heaters and other market transformation policies. 21 refs., 3 figs., 10 tabs.

  8. Modeling patterns of hot water use in households

    SciTech Connect (OSTI)

    Lutz, James D.; Liu, Xiaomin; McMahon, James E.; Dunham, Camilla; Shown, Leslie J.; McCure, Quandra T.

    1996-01-01

    This report presents a detailed model of hot water use patterns in individual households. The model improves upon an existing model by including the effects of four conditions that were previously unaccounted for: the absence of a clothes washer; the absence of a dishwasher; a household consisting of seniors only; and a household that does not pay for its own hot water use. Although these four conditions can significantly affect residential hot water use, and have been noted in other studies, this is the first time that they have been incorporated into a detailed model. This model allows detailed evaluation of the impact of potential efficiency standards for water heaters and other market transformation policies.

  9. New York Household Travel Patterns: A Comparison Analysis

    SciTech Connect (OSTI)

    Hu, Patricia S; Reuscher, Tim

    2007-05-01

    In 1969, the U. S. Department of Transportation began collecting detailed data on personal travel to address various transportation planning issues. These issues range from assessing transportation investment programs to developing new technologies to alleviate congestion. This 1969 survey was the birth of the Nationwide Personal Transportation Survey (NPTS). The survey was conducted again in 1977, 1983, 1990 and 1995. Longer-distance travel was collected in 1977 and 1995. In 2001, the survey was renamed to the National Household Travel Survey (NHTS) and collected both daily and longer-distance trips in one survey. In addition to the number of sample households that the national NPTS/NHTS survey allotted to New York State (NYS), the state procured an additional sample of households in both the 1995 and 2001 surveys. In the 1995 survey, NYS procured an addition sample of more than 9,000 households, increasing the final NY NPTS sample size to a total of 11,004 households. Again in 2001, NYS procured 12,000 additional sample households, increasing the final New York NHTS sample size to a total of 13,423 households with usable data. These additional sample households allowed NYS to address transportation planning issues pertinent to geographic areas significantly smaller than for what the national NPTS and NHTS data are intended. Specifically, these larger sample sizes enable detailed analysis of twelve individual Metropolitan Planning Organizations (MPOs). Furthermore, they allowed NYS to address trends in travel behavior over time. In this report, travel data for the entire NYS were compared to those of the rest of the country with respect to personal travel behavior and key travel determinants. The influence of New York City (NYC) data on the comparisons of the state of New York to the rest of the country was also examined. Moreover, the analysis examined the relationship between population density and travel patterns, and the similarities and differences among New

  10. A Glance at China’s Household Consumption

    SciTech Connect (OSTI)

    Shui, Bin

    2009-10-01

    Known for its scale, China is the most populous country with the world’s third largest economy. In the context of rising living standards, a relatively lower share of household consumption in its GDP, a strong domestic market and globalization, China is witnessing an unavoidable increase in household consumption, related energy consumption and carbon emissions. Chinese policy decision makers and researchers are well aware of these challenges and keen to promote green lifestyles. China has developed a series of energy policies and programs, and launched a wide-range social marketing activities to promote energy conservation.

  11. Shared Solar Projects Powering Households Throughout America | Department

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    of Energy Shared Solar Projects Powering Households Throughout America Shared Solar Projects Powering Households Throughout America January 31, 2014 - 2:30pm Addthis Shared solar projects allow consumers to take advantage of solar energy’s myriad benefits, even though the system is not located on the consumer’s own rooftop. | Photo courtesy of the Vote Solar Initiative Shared solar projects allow consumers to take advantage of solar energy's myriad benefits, even though the system

  12. Household heating bills expected to be lower this winter

    U.S. Energy Information Administration (EIA) Indexed Site

    Household heating bills expected to be lower this winter U.S. consumers are expected to pay less this winter on their home heating bills because of lower oil and natural gas prices and projected milder temperatures than last winter. In its new forecast, the U.S. Energy Information Administration said households that rely on heating oil which are mainly located in the Northeast will pay the lowest heating expenditures in 9 years down 25% from last winter as consumers are expected to save about

  13. Household Vehicles Energy Use: Latest Data and Trends - Table...

    Annual Energy Outlook [U.S. Energy Information Administration (EIA)]

    ... 6.5 1.5 15.4 957 1,031 Income Relative to Poverty Line Below 100 Percent... 7.9 1.4 14.7 942 937...

  14. Heating oil and propane households bills to be lower this winter...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Heating oil and propane households bills to be lower this winter despite recent cold spell Despite the recent cold weather, households that use heating oil or propane as their main ...

  15. ,"Other States Total Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Total Natural Gas Gross Withdrawals and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Other States Total Natural Gas Gross Withdrawals and Production",10,"Monthly","6/2016","01/15/1989" ,"Release Date:","08/31/2016" ,"Next Release

  16. ,"California--State Offshore Natural Gas Gross Withdrawals (MMcf)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Gross Withdrawals (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","California--State Offshore Natural Gas Gross Withdrawals (MMcf)",1,"Annual",2014 ,"Release Date:","08/31/2016" ,"Next Release Date:","09/30/2016" ,"Excel File

  17. ,"Federal Offshore California Natural Gas Gross Withdrawals (MMcf)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Gross Withdrawals (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Federal Offshore California Natural Gas Gross Withdrawals (MMcf)",1,"Annual",2014 ,"Release Date:","08/31/2016" ,"Next Release Date:","09/30/2016" ,"Excel File

  18. ,"Federal Offshore Gulf of Mexico Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Gulf of Mexico Natural Gas Gross Withdrawals and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Federal Offshore Gulf of Mexico Natural Gas Gross Withdrawals and Production",10,"Monthly","6/2016","01/15/1997" ,"Release Date:","08/31/2016" ,"Next Release

  19. Fact #727: May 14, 2012 Nearly Twenty Percent of Households Own Three or

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    More Vehicles | Department of Energy 7: May 14, 2012 Nearly Twenty Percent of Households Own Three or More Vehicles Fact #727: May 14, 2012 Nearly Twenty Percent of Households Own Three or More Vehicles Household vehicle ownership has changed over the last six decades. In 1960, over twenty percent of households did not own a vehicle, but by 2010, that number fell to less than 10%. The number of households with three or more vehicles grew from 2% in 1960 to nearly 20% in 2010. Before 1990,

  20. Fact #729: May 28, 2012 Secondary Household Vehicles Travel Fewer Miles |

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Department of Energy 9: May 28, 2012 Secondary Household Vehicles Travel Fewer Miles Fact #729: May 28, 2012 Secondary Household Vehicles Travel Fewer Miles When a household has more than one vehicle, the secondary vehicles travel fewer miles than the primary vehicle. In a two-vehicle household, the second vehicle travels less than half of the miles that the primary vehicle travels in a day. In a six-vehicle household, the sixth vehicle travels fewer than five miles a day. Daily Vehicle

  1. EmPOWER Maryland Low Income Energy Efficiency Program

    Broader source: Energy.gov [DOE]

    The Maryland Department of Housing and Community Development (DHCD) EmPOWER Maryland Low Income Energy Efficiency Program helps qualifying low-income residents increase the energy efficiency of t...

  2. Better Buildings Residential Network Multifamily & Low-Income...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    ... peerexchange@rossstrategic.com 6 Data & Evaluation Financing & Revenue Marketing & Outreach Multifamily Low-Income Housing Program Sustainability ...

  3. INCOMING DOCUMENT CONTROL FORM DOCUMENT DESCRIPTION ORGANIZATIO

    Office of Legacy Management (LM)

    INCOMING DOCUMENT CONTROL FORM DOCUMENT DESCRIPTION ORGANIZATIO )ATE COMPLETED: ACTION NUMBER: I ! I I DOCUMENT CONTROL DATE INITIALS DATA BASE: ACTION LOG: FILED: To : Doug Tonkay, OTS Decen From: MIchele Landis, dRW Subject: Draft report ~ Result= of the Radiologic; Former Ore Storage Site, Palmerton, Pennsylvania Attached is one copy of the draft report. PIE provide your comments to me by January 16, 1990. tlichele Landis ,9, 1989 "ey at the review and Results of the Radiological SJrvey

  4. Gross error detection and stage efficiency estimation in a separation process

    SciTech Connect (OSTI)

    Serth, R.W.; Srikanth, B. . Dept. of Chemical and Natural Gas Engineering); Maronga, S.J. . Dept. of Chemical and Process Engineering)

    1993-10-01

    Accurate process models are required for optimization and control in chemical plants and petroleum refineries. These models involve various equipment parameters, such as stage efficiencies in distillation columns, the values of which must be determined by fitting the models to process data. Since the data contain random and systematic measurement errors, some of which may be large (gross errors), they must be reconciled to obtain reliable estimates of equipment parameters. The problem thus involves parameter estimation coupled with gross error detection and data reconciliation. MacDonald and Howat (1988) studied the above problem for a single-stage flash distillation process. Their analysis was based on the definition of stage efficiency due to Hausen, which has some significant disadvantages in this context, as discussed below. In addition, they considered only data sets which contained no gross errors. The purpose of this article is to extend the above work by considering alternative definitions of state efficiency and efficiency estimation in the presence of gross errors.

  5. Household Vehicles Energy Use: Latest Data and Trends - Table...

    Gasoline and Diesel Fuel Update (EIA)

    ... 9.6 5.0 100 4.4 6.2 4.5 0.8 6.8 4.5 Income Relative to Poverty Line Below 100 Percent... 11.4 6.0 116 5.1 5.6...

  6. U.S. Natural Gas Gross Withdrawals Offshore (Million Cubic Feet)

    U.S. Energy Information Administration (EIA) Indexed Site

    Gross Withdrawals Offshore (Million Cubic Feet) U.S. Natural Gas Gross Withdrawals Offshore (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 3,932,196 5,111,413 5,603,025 1980's 5,650,097 5,693,432 5,466,050 4,734,843 5,220,061 4,631,756 4,588,565 5,078,178 5,180,875 5,231,028 1990's 5,509,312 5,308,457 5,324,039 5,373,300 5,700,666 5,431,665 5,843,661 5,906,329 5,800,561 5,689,438 2000's 5,699,377 5,815,542 5,312,348 5,215,683 4,736,252

  7. Floating Offshore Wind in California: Gross Potential for Jobs and Economic Impacts from Two Future Scenarios

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Floating Offshore Wind in California: Gross Potential for Jobs and Economic Impacts from Two Future Scenarios Bethany Speer, David Keyser, and Suzanne Tegen National Renewable Energy Laboratory This report is available from the Bureau of Ocean Energy Management by referencing OCS Study BOEM 2016-029. The report may be downloaded from BOEM's Recently Completed Environmental Studies - Pacific webpage at http://www.boem.gov/Pacific-Completed-Studies/. This study was funded by the U.S. Department of

  8. DOE Zero Ready Home Case Study: Promethean Homes, Gross-Shepard Residence, Charlottesville, VA

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Promethean Homes Gross-Shepard Residence Charlottesville, VA DOE ZERO ENERGY READY HOME(tm) The U.S. Department of Energy invites home builders across the country to meet the extraordinary levels of excellence and quality specified in DOE's Zero Energy Ready Home program (formerly known as Challenge Home). Every DOE Zero Energy Ready Home starts with ENERGY STAR Certified Homes Version 3.0 for an energy-efficient home built on a solid foundation of building science research. Advanced

  9. Household Vehicles Energy Use: Latest Data and Trends - Table...

    Annual Energy Outlook [U.S. Energy Information Administration (EIA)]

    11.5 0.8 1.0 0.9 0.8 0.7 0.8 0.7 1.6 1.4 0.8 0.5 0.2 0.1 0.7 0.4 Income Relative to Poverty Line Below 100 Percent... 13.3 0.3 0.4 0.4 0.6...

  10. Fact #614: March 15, 2010 Average Age of Household Vehicles | Department of

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Energy 4: March 15, 2010 Average Age of Household Vehicles Fact #614: March 15, 2010 Average Age of Household Vehicles The average age of household vehicles has increased from 6.6 years in 1977 to 9.2 years in 2009. Pickup trucks have the oldest average age in every year listed. Sport utility vehicles (SUVs), first reported in the 1995 survey, have the youngest average age. Average Vehicle Age by Vehicle Type Graph showing the average vehicle age by type (car, van, pickup, SUV, all household

  11. Better Buildings Residential Multifamily/Low-Income Peer Exchange...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    ... revenue on housing, increasing their motivation to save money on energy. Low-income ... were effective? Did your organization try any outreach strategies that did not work? ...

  12. Approaches to Electric Utility Energy Efficiency for Low Income...

    Open Energy Info (EERE)

    Approaches to Electric Utility Energy Efficiency for Low Income Customers in a Changing Regulatory Environment Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Approaches...

  13. The Denver Energy Challenge-- Serving Moderate Income Residents

    Broader source: Energy.gov [DOE]

    Provides an overview of the Denver Energy Challenge and how services were expanded to moderate income residents including challenges and next steps.

  14. Alternative Energy and Energy Conservation Patent Income Tax...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Personal) Alternative Energy and Energy Conservation Patent Income Tax Deduction (Personal) < Back Eligibility Residential Savings Category Solar - Passive Solar Water Heat Solar...

  15. Alternative Energy and Energy Conservation Patent Income Tax...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Corporate) Alternative Energy and Energy Conservation Patent Income Tax Deduction (Corporate) < Back Eligibility Commercial Savings Category Solar - Passive Solar Water Heat Solar...

  16. Effective Energy Behavior Change for Low-Income Weatherization Clients

    Broader source: Energy.gov [DOE]

    This document contains the transcript for the Effective Energy Behavior Change for Low-Income Weatherization Clients webinar presented on May 31, 2012.

  17. Better Buildings Program San Jose -- Serving Moderate Income...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Better Buildings Program San Jose -- Serving Moderate Income Residents Provides an overview of the program components and goals, including the whole neighborhood approach pilot ...

  18. Better Buildings Challenge: Clean Energy Low Income Accelerator

    Broader source: Energy.gov [DOE]

    This program aims to lower energy bills in low-income communities through the expanded installation of energy efficiency and distributed renewables. Partners are able to leverage the experience of others who are concurrently developing new partnerships, investigating successful models, and developing local plans that could meet state or local climate and energy goals for low income communities.

  19. A material flow analysis on current electrical and electronic waste disposal from Hong Kong households

    SciTech Connect (OSTI)

    Lau, Winifred Ka-Yan; Chung, Shan-Shan; Zhang, Chan

    2013-03-15

    Highlights: ► Most household TWARC waste is sold directly to private e-waste collectors in HK. ► The current e-waste recycling network is popular with HK households. ► About 80% of household generated TWARC is exported overseas each year. ► Over 7000 tonnes/yr of household generated TWARC reach landfills. ► It is necessary to upgrade safety and awareness in HK’s e-waste recycling industry. - Abstract: A material flow study on five types of household electrical and electronic equipment, namely television, washing machine, air conditioner, refrigerator and personal computer (TWARC) was conducted to assist the Government of Hong Kong to establish an e-waste take-back system. This study is the first systematic attempt on identifying key TWARC waste disposal outlets and trade practices of key parties involved in Hong Kong. Results from two questionnaire surveys, on local households and private e-waste traders, were used to establish the material flow of household TWARC waste. The study revealed that the majority of obsolete TWARC were sold by households to private e-waste collectors and that the current e-waste collection network is efficient and popular with local households. However, about 65,000 tonnes/yr or 80% of household generated TWARC waste are being exported overseas by private e-waste traders, with some believed to be imported into developing countries where crude recycling methods are practiced. Should Hong Kong establish a formal recycling network with tight regulatory control on imports and exports, the potential risks of current e-waste recycling practices on e-waste recycling workers, local residents and the environment can be greatly reduced.

  20. ,"Kansas Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Kansas Natural Gas Gross Withdrawals and Production",10,"Monthly","6/2016","01/15/1989" ,"Release Date:","08/31/2016" ,"Next Release Date:","09/30/2016" ,"Excel File

  1. ,"Louisiana Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Louisiana Natural Gas Gross Withdrawals and Production",10,"Monthly","6/2016","01/15/1989" ,"Release Date:","08/31/2016" ,"Next Release Date:","09/30/2016" ,"Excel File

  2. ,"Maryland Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Maryland Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","6/2016" ,"Release Date:","8/31/2016" ,"Next Release Date:","9/30/2016" ,"Excel File

  3. ,"Michigan Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Michigan Natural Gas Gross Withdrawals and Production",10,"Monthly","6/2016","01/15/1989" ,"Release Date:","08/31/2016" ,"Next Release Date:","09/30/2016" ,"Excel File

  4. ,"Montana Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Montana Natural Gas Gross Withdrawals and Production",10,"Monthly","6/2016","01/15/1989" ,"Release Date:","08/31/2016" ,"Next Release Date:","09/30/2016" ,"Excel File

  5. ,"Nebraska Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Nebraska Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","6/2016" ,"Release Date:","8/31/2016" ,"Next Release Date:","9/30/2016" ,"Excel File

  6. ,"New Mexico Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","New Mexico Natural Gas Gross Withdrawals and Production",10,"Monthly","6/2016","01/15/1989" ,"Release Date:","08/31/2016" ,"Next Release Date:","09/30/2016" ,"Excel File

  7. ,"North Dakota Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","North Dakota Natural Gas Gross Withdrawals and Production",10,"Monthly","6/2016","01/15/1989" ,"Release Date:","08/31/2016" ,"Next Release Date:","09/30/2016" ,"Excel File

  8. ,"Ohio Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Ohio Natural Gas Gross Withdrawals and Production",10,"Monthly","6/2016","01/15/1991" ,"Release Date:","08/31/2016" ,"Next Release Date:","09/30/2016" ,"Excel File

  9. ,"Oklahoma Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Oklahoma Natural Gas Gross Withdrawals and Production",10,"Monthly","6/2016","01/15/1989" ,"Release Date:","08/31/2016" ,"Next Release Date:","09/30/2016" ,"Excel File

  10. ,"Oregon Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Oregon Natural Gas Gross Withdrawals and Production",10,"Monthly","6/2016","01/15/1991" ,"Release Date:","08/31/2016" ,"Next Release Date:","09/30/2016" ,"Excel File

  11. ,"Pennsylvania Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Pennsylvania Natural Gas Gross Withdrawals and Production",10,"Monthly","6/2016","01/15/1991" ,"Release Date:","08/31/2016" ,"Next Release Date:","09/30/2016" ,"Excel File

  12. ,"Pennsylvania Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Pennsylvania Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","6/2016" ,"Release Date:","8/31/2016" ,"Next Release Date:","9/30/2016" ,"Excel File

  13. ,"Texas Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas Natural Gas Gross Withdrawals and Production",10,"Monthly","6/2016","01/15/1989" ,"Release Date:","08/31/2016" ,"Next Release Date:","09/30/2016" ,"Excel File

  14. ,"U.S. Natural Gas Gross Withdrawals Offshore (MMcf)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Offshore (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","U.S. Natural Gas Gross Withdrawals Offshore (MMcf)",1,"Annual",2014 ,"Release Date:","08/31/2016" ,"Next Release Date:","09/30/2016" ,"Excel File Name:","na1090_nus_2a.xls" ,"Available

  15. ,"Utah Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Utah Natural Gas Gross Withdrawals and Production",10,"Monthly","6/2016","01/15/1989" ,"Release Date:","08/31/2016" ,"Next Release Date:","09/30/2016" ,"Excel File

  16. ,"West Virginia Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","West Virginia Natural Gas Gross Withdrawals and Production",10,"Monthly","6/2016","01/15/1991" ,"Release Date:","08/31/2016" ,"Next Release Date:","09/30/2016" ,"Excel File

  17. ,"Wyoming Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Wyoming Natural Gas Gross Withdrawals and Production",10,"Monthly","6/2016","01/15/1989" ,"Release Date:","08/31/2016" ,"Next Release Date:","09/30/2016" ,"Excel File

  18. OSTIblog Articles in the David Gross Topic | OSTI, US Dept of Energy Office

    Office of Scientific and Technical Information (OSTI)

    of Scientific and Technical Information David Gross Topic 100th DOE R&D Accomplishments Feature Page Celebration by Linda McBrearty 07 Jul, 2013 in Products and Content 7566 Accomp100_slide.preview.jpg 100th DOE R&D Accomplishments Feature Page Celebration Read more about 7566 DOE R&D Accomplishments is a unique website and database in the OSTI collection. For over 14 years, special Feature pages have been methodically researched and useful information collected on scientists,

  19. Soliton solutions of the 3D Gross-Pitaevskii equation by a potential control method

    SciTech Connect (OSTI)

    Fedele, R.; Eliasson, B.; Shukla, P. K.; Haas, F.; Jovanovic, D.; De Nicola, S.

    2010-12-14

    We present a class of three-dimensional solitary waves solutions of the Gross-Pitaevskii (GP) equation, which governs the dynamics of Bose-Einstein condensates (BECs). By imposing an external controlling potential, a desired time-dependent shape of the localized BEC excitation is obtained. The stability of some obtained localized solutions is checked by solving the time-dependent GP equation numerically with analytic solutions as initial conditions. The analytic solutions can be used to design external potentials to control the localized BECs in experiment.

  20. ,"Alaska Natural Gas Gross Withdrawals Total Offshore (MMcf)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Total Offshore (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Alaska Natural Gas Gross Withdrawals Total Offshore (MMcf)",1,"Annual",2014 ,"Release Date:","08/31/2016" ,"Next Release Date:","09/30/2016" ,"Excel File Name:","na1090_sak_2a.xls"

  1. ,"California Natural Gas Gross Withdrawals Total Offshore (MMcf)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Total Offshore (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","California Natural Gas Gross Withdrawals Total Offshore (MMcf)",1,"Annual",2014 ,"Release Date:","08/31/2016" ,"Next Release Date:","09/30/2016" ,"Excel File Name:","na1090_sca_2a.xls"

  2. ,"California Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","California Natural Gas Gross Withdrawals and Production",10,"Monthly","6/2016","01/15/1989" ,"Release Date:","08/31/2016" ,"Next Release Date:","09/30/2016" ,"Excel File

  3. ,"California Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","California Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","6/2016" ,"Release Date:","8/31/2016" ,"Next Release Date:","9/30/2016" ,"Excel File

  4. ,"Colorado Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Colorado Natural Gas Gross Withdrawals and Production",10,"Monthly","6/2016","01/15/1989" ,"Release Date:","08/31/2016" ,"Next Release Date:","09/30/2016" ,"Excel File

  5. ,"Colorado Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Colorado Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","6/2016" ,"Release Date:","8/31/2016" ,"Next Release Date:","9/30/2016" ,"Excel File

  6. ,"Florida Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Florida Natural Gas Gross Withdrawals and Production",10,"Monthly","6/2016","01/15/1989" ,"Release Date:","08/31/2016" ,"Next Release Date:","09/30/2016" ,"Excel File

  7. ,"Florida Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Florida Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","6/2016" ,"Release Date:","8/31/2016" ,"Next Release Date:","9/30/2016" ,"Excel File

  8. ,"Illinois Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Illinois Natural Gas Gross Withdrawals and Production",10,"Monthly","6/2016","01/15/1991" ,"Release Date:","08/31/2016" ,"Next Release Date:","09/30/2016" ,"Excel File

  9. ,"Illinois Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Illinois Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","6/2016" ,"Release Date:","8/31/2016" ,"Next Release Date:","9/30/2016" ,"Excel File

  10. ,"Indiana Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Indiana Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","6/2016" ,"Release Date:","8/31/2016" ,"Next Release Date:","9/30/2016" ,"Excel File

  11. 55,"Aberdeen City of",5,1,482619,"Taxes Other Than Income Taxes...

    U.S. Energy Information Administration (EIA) Indexed Site

    ... 14, less line 19)" 230,"Albany Water Gas & Light Comm",5,1,4952607,"Taxes Other Than Income Taxes, Operating Income (408.1)" 230,"Albany Water Gas & Light Comm",5,2,0,"Income ...

  12. 55,"Aberdeen City of",5,1,479437,"Taxes Other Than Income Taxes...

    U.S. Energy Information Administration (EIA) Indexed Site

    ... 14, less line 19)" 230,"Albany Water Gas & Light Comm",5,1,4930279,"Taxes Other Than Income Taxes, Operating Income (408.1)" 230,"Albany Water Gas & Light Comm",5,2,0,"Income ...

  13. Laboratory Testing of Demand-Response Enabled Household Appliances

    SciTech Connect (OSTI)

    Sparn, B.; Jin, X.; Earle, L.

    2013-10-01

    With the advent of the Advanced Metering Infrastructure (AMI) systems capable of two-way communications between the utility's grid and the building, there has been significant effort in the Automated Home Energy Management (AHEM) industry to develop capabilities that allow residential building systems to respond to utility demand events by temporarily reducing their electricity usage. Major appliance manufacturers are following suit by developing Home Area Network (HAN)-tied appliance suites that can take signals from the home's 'smart meter,' a.k.a. AMI meter, and adjust their run cycles accordingly. There are numerous strategies that can be employed by household appliances to respond to demand-side management opportunities, and they could result in substantial reductions in electricity bills for the residents depending on the pricing structures used by the utilities to incent these types of responses. The first step to quantifying these end effects is to test these systems and their responses in simulated demand-response (DR) conditions while monitoring energy use and overall system performance.

  14. Laboratory Testing of Demand-Response Enabled Household Appliances

    SciTech Connect (OSTI)

    Sparn, B.; Jin, X.; Earle, L.

    2013-10-01

    With the advent of the Advanced Metering Infrastructure (AMI) systems capable of two-way communications between the utility's grid and the building, there has been significant effort in the Automated Home Energy Management (AHEM) industry to develop capabilities that allow residential building systems to respond to utility demand events by temporarily reducing their electricity usage. Major appliance manufacturers are following suit by developing Home Area Network (HAN)-tied appliance suites that can take signals from the home's 'smart meter,' a.k.a. AMI meter, and adjust their run cycles accordingly. There are numerous strategies that can be employed by household appliances to respond to demand-side management opportunities, and they could result in substantial reductions in electricity bills for the residents depending on the pricing structures used by the utilities to incent these types of responses.The first step to quantifying these end effects is to test these systems and their responses in simulated demand-response (DR) conditions while monitoring energy use and overall system performance.

  15. Fact #616: March 29, 2010 Household Vehicle-Miles of Travel by Trip Purpose

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    | Department of Energy 6: March 29, 2010 Household Vehicle-Miles of Travel by Trip Purpose Fact #616: March 29, 2010 Household Vehicle-Miles of Travel by Trip Purpose In 2009, getting to and from work accounted for about 27% of household vehicle-miles of travel (VMT). Work-related business was 8.4% of VMT in 2001, but declined to 6.7% in 2009, possibly due to advancements in computing technology making it possible for more business to be handled electronically. VMT for shopping was almost

  16. Tailored Marketing for Low-income and Under-Represented Population...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Tailored Marketing for Low-income and Under-Represented Population Segments (201) Tailored Marketing for Low-income and Under-Represented Population Segments (201) Better Buildings ...

  17. The Farmer's Conundrum: Income from Biofuels or Protect the Soil?

    Broader source: Energy.gov [DOE]

    Selling crop residues for bioenergy could provide farmers with an extra source of income, but leaving some residue on the fields has benefits too. So how can land managers find this balance?

  18. Empire District Electric- Low Income New Homes Program

    Broader source: Energy.gov [DOE]

    Empire District Electric offers rebates for energy efficient measures and appliances in new, low-income homes. Rebates are available for several types of building insulation, heat pumps, central...

  19. Wind Development Found to Increase County-Level Personal Income...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Wind Development Found to Increase County-Level Personal Income January 10, 2013 - 2:21pm Addthis This is an excerpt from the Fourth Quarter 2012 edition of the Wind Program R&D ...

  20. Figure ES2. Annual Indices of Real Disposable Income, Vehicle...

    U.S. Energy Information Administration (EIA) Indexed Site

    ES2 Figure ES2. Annual Indices of Real Disposable Income, Vehicle-Miles Traveled, Consumer Price Index (CPI-U), and Real Average Retail Gasoline Price, 1978-2004, 1985100...

  1. Income Tax Deduction for Energy-Efficient Products | Department...

    Broader source: Energy.gov (indexed) [DOE]

    may deduct from their taxable personal income an amount equal to 20% of the sales taxes paid for certain energy efficient equipment. The incentive is capped at 500. This...

  2. Income Tax Deduction for the Installation of Building Insulation

    Office of Energy Efficiency and Renewable Energy (EERE)

    A residential taxpayer is entitled to an Indiana income tax deduction on the materials and labor used to install insulation in a taxpayer’s principal place of residence in Indiana. 

  3. Better Buildings Program San Jose -- Serving Moderate Income Residents |

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Department of Energy Program San Jose -- Serving Moderate Income Residents Better Buildings Program San Jose -- Serving Moderate Income Residents Provides an overview of the program components and goals, including the whole neighborhood approach pilot which aims to streamline participant, contractor, and administration processes for neighborhood retrofitting in order to reduce high transaction costs created by the current one-off delivery model. San Jose Program Presentation (3.53 MB) More

  4. Table 2.5 Household Energy Consumption and Expenditures by End...

    U.S. Energy Information Administration (EIA) Indexed Site

    5 Household 1 Energy Consumption and Expenditures by End Use, Selected Years, 1978-2005 Year Space ... 3 Fuel Oil 4 LPG 5 Total Electricity 3 Natural Gas Elec- tricity 3 ...

  5. How Do You Encourage Everyone in Your Household to Save Energy?

    Broader source: Energy.gov [DOE]

    Anyone who has decided to save energy at home knows that the entire household needs to be involved if you really want to see savings. Some people—be they roommates, spouses, children, or maybe even...

  6. Competition Helps Kids Learn About Energy and Save Their Households Some

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Money | Department of Energy Competition Helps Kids Learn About Energy and Save Their Households Some Money Competition Helps Kids Learn About Energy and Save Their Households Some Money May 21, 2013 - 2:40pm Addthis Students can register now to save energy and win prizes with the Home Energy Challenge. Students can register now to save energy and win prizes with the Home Energy Challenge. Eric Barendsen Energy Technology Program Specialist, Office of Energy Efficiency and Renewable Energy

  7. Residential Network Members Impact More Than 42,000 Households | Department

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    of Energy Impact More Than 42,000 Households Residential Network Members Impact More Than 42,000 Households Photo of a row of townhomes. Eligible Better Buildings Residential Network members reported completing 27,563 home energy upgrades during 2013 as part of the Residential Network's first reporting cycle. In addition, 13 Better Buildings Neighborhood Program partners completed 12,166 home energy upgrades, and six Home Performance with ENERGY STAR® Sponsors completed 2,540 home energy

  8. A Mixed Nordic Experience: Implementing Competitive Retail Electricity Markets for Household Customers

    SciTech Connect (OSTI)

    Olsen, Ole Jess; Johnsen, Tor Arnt; Lewis, Philip

    2006-11-15

    Although the Nordic countries were among the first to develop competition in the electricity industry, it took a long time to make retail competition work. In Norway and Sweden a considerable number of households are actively using the market but very few households are active in Finland and Denmark. One problem has been institutional barriers involving metering, limited unbundling of distribution and supply, and limited access to reliable information on contracts and prices. (author)

  9. Missouri Natural Gas Gross Withdrawals from Oil Wells (Million Cubic Feet)

    Gasoline and Diesel Fuel Update (EIA)

    Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2007 0 0 0 0 0 0 0 0 0 0 0 0 2008 NA NA NA NA NA NA NA NA NA NA NA NA 2009 NA NA NA NA NA NA NA NA NA NA NA NA 2010 NA NA NA NA NA NA NA NA NA NA NA NA 2011 NA NA NA NA NA NA NA NA NA NA NA NA 2012 NA NA NA NA NA NA NA NA NA NA NA NA 2013 0 0 0 0 0 0 0 0 0 0 0 0 2014 0 0 0 0 0 0 0 0 0 0 0 0 2015 NA NA NA NA NA NA NA NA NA NA NA NA 2016 NA NA NA NA NA NA

    from Oil Wells (Million Cubic Feet) Missouri Natural Gas Gross Withdrawals

  10. 1990 yearly calibration of Pacific Northwest Laboratory's gross-gamma borehole geophysical logging system

    SciTech Connect (OSTI)

    Arthur, R.J.

    1990-08-01

    This report describes the 1990 yearly calibration of a gross-gamma geophysical pulse logging system owned by the US Department of Energy (DOE) and operated by Pacific Northwest Laboratory (PNL). The calibration was conducted to permit the continued use of this system for geological and hydrologic studies associated with remedial investigation at the Hanford Site. Primary calibrations to equivalent uranium units were conducted in borehole model standards that were recently moved to the Hanford Site from the DOE field calibration facility in Spokane, Washington. The calibrations were performed in borehole models SBL/SBH and SBA/SBB, which contain low equivalent-uranium concentrations. The integrity of the system throughout the previous year from gamma-ray monitoring was demonstrated using the before- and after-logging field calibration readings with the field source in calibration Positions 1 and 2. Most of the Position 1 readings are within an 8% limit that is set by the governing PNL technical reference procedure as a critical value above which the instrument is considered suspect. Many of the Position 2 readings exceed the 8% limit; however, the fluctuation was traced to field-source geometry variability that affected Position 1 count rates by up to 6% and Position 2 count rates by as much as 16%. Correlations were established based on two similar approaches for relating observed count rate in before- and after-logging field calibrations to equivalent uranium concentrations. The temperature drift of the gamma-ray probe was documented and amounts to less than 0.1%/{degree}C within the temperature range 0{degree}C to 42{degree}C. The low-energy cutoff for the gross gamma-ray probe was determined to be between 46.5 and 59.5 keV. 10 refs., 4 figs., 13 tabs.

  11. Improving Demographic Components of Integrated Assessment Models: The Effect of Changes in Population Composition by Household Characteristics

    SciTech Connect (OSTI)

    Brian C. O'Neill

    2006-08-09

    This report describes results of the research project on "Improving Demographic Components of Integrated Assessment Models: The Effect of Changes in Population Composition by Household Characteristics". The overall objective of this project was to improve projections of energy demand and associated greenhouse gas emissions by taking into account demographic factors currently not incorporated in Integrated Assessment Models (IAMs) of global climate change. We proposed to examine the potential magnitude of effects on energy demand of changes in the composition of populations by household characteristics for three countries: the U.S., China, and Indonesia. For each country, we planned to analyze household energy use survey data to estimate relationships between household characteristics and energy use; develop a new set of detailed household projections for each country; and combine these analyses to produce new projections of energy demand illustrating the potential importance of consideration of households.

  12. Development of the household sample for furnace and boilerlife-cycle cost analysis

    SciTech Connect (OSTI)

    Whitehead, Camilla Dunham; Franco, Victor; Lekov, Alex; Lutz, Jim

    2005-05-31

    Residential household space heating energy use comprises close to half of all residential energy consumption. Currently, average space heating use by household is 43.9 Mbtu for a year. An average, however, does not reflect regional variation in heating practices, energy costs, or fuel type. Indeed, a national average does not capture regional or consumer group cost impacts from changing efficiency levels of heating equipment. The US Department of Energy sets energy standards for residential appliances in, what is called, a rulemaking process. The residential furnace and boiler efficiency rulemaking process investigates the costs and benefits of possible updates to the current minimum efficiency regulations. Lawrence Berkeley National Laboratory (LBNL) selected the sample used in the residential furnace and boiler efficiency rulemaking from publically available data representing United States residences. The sample represents 107 million households in the country. The data sample provides the household energy consumption and energy price inputs to the life-cycle cost analysis segment of the furnace and boiler rulemaking. This paper describes the choice of criteria to select the sample of houses used in the rulemaking process. The process of data extraction is detailed in the appendices and is easily duplicated. The life-cycle cost is calculated in two ways with a household marginal energy price and a national average energy price. The LCC results show that using an national average energy price produces higher LCC savings but does not reflect regional differences in energy price.

  13. Revenue phase-in plans equal deferred taxable income

    SciTech Connect (OSTI)

    Beck, D.E.

    1994-04-01

    Recently, utilities seeking rate increases have submitted innovative petitions for phase-in rate relief to state regulators. According to the Edison Electric Institute, the industry has seen almost 80 phase-in rate orders issued nation-wide in the last six years. For financial reporting purposes, deferred revenues under phase-in plans must be recognized as current income in the first year of the phase-in. The Internal Revenue Service (IRS) at the Industry Coordinator level, however, recently accepted the position that deferred phase-in revenues accrued for book purposes are not immediately taxable income to the utility.

  14. Table 2. Real Gross Domestic Product Growth Trends, Projected vs. Actual

    U.S. Energy Information Administration (EIA) Indexed Site

    Real Gross Domestic Product Growth Trends, Projected vs. Actual Projected Real GDP Growth Trend (cumulative average percent growth in projected real GDP from first year shown for each AEO) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 3.09 3.15 2.86 2.78 2.73 2.65 2.62 2.60 2.56 2.53 2.52 2.49 2.45 2.41 2.40 2.36 2.32 2.29 AEO 1995 3.66 2.77 2.53 2.71 2.67 2.61 2.55 2.48 2.46 2.45 2.45 2.43 2.39 2.35 2.31 2.27 2.24 AEO 1996 2.61

  15. Other States Natural Gas Gross Withdrawals from Shale Gas (Million Cubic

    U.S. Energy Information Administration (EIA) Indexed Site

    Feet) Shale Gas (Million Cubic Feet) Other States Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2007 13,204 11,926 13,204 12,778 13,204 12,778 13,204 13,204 12,778 13,204 12,778 13,204 2008 12,755 11,932 12,755 12,343 12,755 12,343 12,755 12,755 12,343 12,755 12,343 12,755 2009 12,222 11,039 12,222 11,827 12,222 11,827 12,222 12,222 11,827 12,222 11,827 12,222 2010 11,842 10,659 11,705 11,180 11,541 11,189 11,357 11,589

  16. Failure of the gross theory of beta decay in neutron deficient nuclei

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Firestone, R. B.; Schwengner, R.; Zuber, K.

    2015-05-28

    The neutron deficient isotopes 117-121Xe, 117-124Cs, and 122-124Ba were produced by a beam of 28Si from the LBNL SuperHILAC on a target of natMo. The isotopes were mass separated and their beta decay schemes were measured with a Total Absorption Spectrometer (TAS). The beta strengths derived from these data decreased dramatically to levels above ≈1 MeV for the even-even decays; 3–4 MeV for even-Z, odd-N decays; 4–5 MeV for the odd-Z, even-N decays; and 7–8 MeV for the odd-Z, odd-N decays. The decreasing strength to higher excitation energies in the daughters contradicts the predictions of the Gross Theory of Betamore » Decay. The integrated beta strengths are instead found to be consistent with shell model predictions where the single-particle beta strengths are divided amoung many low-lying levels. The experimental beta strengths determined here have been used calculate the half-lives of 143 neutron deficient nuclei with Z=51–64 to a precision of 20% with respect to the measured values.« less

  17. Failure of the gross theory of beta decay in neutron deficient nuclei

    SciTech Connect (OSTI)

    Firestone, R. B.; Schwengner, R.; Zuber, K.

    2015-05-28

    The neutron deficient isotopes 117-121Xe, 117-124Cs, and 122-124Ba were produced by a beam of 28Si from the LBNL SuperHILAC on a target of natMo. The isotopes were mass separated and their beta decay schemes were measured with a Total Absorption Spectrometer (TAS). The beta strengths derived from these data decreased dramatically to levels above ?1 MeV for the even-even decays; 34 MeV for even-Z, odd-N decays; 45 MeV for the odd-Z, even-N decays; and 78 MeV for the odd-Z, odd-N decays. The decreasing strength to higher excitation energies in the daughters contradicts the predictions of the Gross Theory of Beta Decay. The integrated beta strengths are instead found to be consistent with shell model predictions where the single-particle beta strengths are divided amoung many low-lying levels. The experimental beta strengths determined here have been used calculate the half-lives of 143 neutron deficient nuclei with Z=5164 to a precision of 20% with respect to the measured values.

  18. Nevada Natural Gas Gross Withdrawals from Gas Wells (Million Cubic Feet)

    Gasoline and Diesel Fuel Update (EIA)

    Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2006 0 0 0 0 0 0 0 0 0 0 0 0 2007 0 0 0 0 0 0 0 0 0 0 0 0 2008 0 0 0 0 0 0 0 0 0 0 0 0 2009 0 0 0 0 0 0 0 0 0 0 0 0 2010 0 0 0 0 0 0 0 0 0 0 0 0 2011 0 0 0 0 0 0 0 0 0 0 0 0 2012 0 0 0 0 0 0 0 0 0 0 0 0 2013 0 0 0 0 0 0 0 0 0 0 0 0 2014 0 0 0 0 0 0 0 0 0 0 0 0 2015 NA NA NA NA NA NA NA NA NA NA NA NA 2016 NA NA NA NA NA NA

    from Gas Wells (Million Cubic Feet) Nevada Natural Gas Gross Withdrawals from Gas Wells (Million Cubic Feet)

  19. New Mexico Natural Gas Gross Withdrawals from Coalbed Wells (Million Cubic

    Gasoline and Diesel Fuel Update (EIA)

    Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 40,256 45,534 43,018 2000's 46,885 48,981 37,324 37,849 30,817 41,207 55,506 61,050 68,742 70,102 2010's 70,694 73,379 74,357 74,817 75,726 77,947

    10 2011 2012 2013 2014 2015 View History Gross Withdrawals 1,341,475 1,287,682 1,276,296 1,247,394 1,265,579 1,289,908 1967-2015 From Gas Wells 616,134 556,024 653,057 588,127 535,181 1967-2014 From Oil Wells 238,580 252,326 127,009 160,649 204,054

  20. Suppressed gross erosion of high-temperature lithium via rapid deuterium implantation

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Abrams, T.; Jaworski, M. A.; Chen, M.; Carter, E. A.; Kaita, R.; Stotler, D. P.; De Temmerman, G.; Morgan, T. W.; van den Berg, M. A.; van der Meiden, H. J.

    2015-12-17

    Lithium-coated high-Z substrates are planned for use in the NSTX-U divertor and are a candidate plasma facing component (PFC) for reactors, but it remains necessary to characterize the gross Li erosion rate under high plasma fluxes (>1023 m-2 s-1), typical for the divertor region. In this work, a realistic model for the compositional evolution of a Li/D layer is developed that incorporates first principles molecular dynamics (MD) simulations of D diffusion in liquid Li. Predictions of Li erosion from a mixed Li/D material are also developed that include formation of lithium deuteride (LiD). The erosion rate of Li from LiDmore » is predicted to be significantly lower than from pure Li. This prediction is tested in the Magnum-PSI linear plasma device at ion fluxes of 1023-1024 m-2 s-1 and Li surface temperatures. ≤800 °C. Li/LiD coatings ranging in thickness from 0.2 to 500 μm are studied. The dynamic D/Li concentrations are inferred via diffusion simulations. The pure Li erosion rate remains greater than Langmuir Law evaporation, as expected. For mixed-material Li/LiD surfaces, the erosion rates are reduced, in good agreement with modelling in almost all cases. Lastly, these results imply that the temperature limit for a Li-coated PFC may be significantly higher than previously imagined.« less

  1. Weak decay processes in pre-supernova core evolution within the gross theory

    SciTech Connect (OSTI)

    Ferreira, R. C.; Dimarco, A. J.; Samana, A. R.; Barbero, C. A.

    2014-03-20

    The beta decay and electron capture rates are of fundamental importance in the evolution of massive stars in a pre-supernova core. The beta decay process gives its contribution by emitting electrons in the plasma of the stellar core, thereby increasing pressure, which in turn increases the temperature. From the other side, the electron capture removes free electrons from the plasma of the star core contributing to the reduction of pressure and temperature. In this work we calculate the beta decay and electron capture rates in stellar conditions for 63 nuclei of relevance in the pre-supernova stage, employing Gross Theory as the nuclear model. We use the abundances calculated with the Saha equations in the hypothesis of nuclear statistical equilibrium to evaluate the time derivative of the fraction of electrons. Our results are compared with other evaluations available in the literature. They have shown to be one order less or equal than the calculated within other models. Our results indicate that these differences may influence the evolution of the star in the later stages of pre-supernova.

  2. Table 4

    U.S. Energy Information Administration (EIA) Indexed Site

    9. Mean Annual Electricity Consumption for Lighting, by Family Income by Number of Household Members, 1993 (Kilowatthours) Number of Household Members Family Income All Households...

  3. Buildings Energy Data Book: 2.9 Low-Income Housing

    Buildings Energy Data Book [EERE]

    6 Weatherization Costs and Savings - DOE Weatherization program requires that States spend no more than an average of $6,572 per household in PY 2011. All States are using energy audits or priority lists to determine the most cost-effective weatherization measures. - DOE weatherization created an average energy savings of $437 per household, reduced household annual annual consumption by 35% and returned savings of $1.80 per every $1 invested. Source(s): DOE, Weatherization and Intergovernmental

  4. NYSERDA's Green Jobs-Green New York Program: Extending Energy Efficiency Financing To Underserved Households

    SciTech Connect (OSTI)

    Zimring, Mark; Fuller, Merrian

    2011-01-24

    The New York legislature passed the Green Jobs-Green New York (GJGNY) Act in 2009. Administered by the New York State Energy Research and Development Authority (NYSERDA), GJGNY programs provide New Yorkers with access to free or low-cost energy assessments,1 energy upgrade services,2 low-cost financing, and training for various 'green-collar' careers. Launched in November 2010, GJGNY's residential initiative is notable for its use of novel underwriting criteria to expand access to energy efficiency financing for households seeking to participate in New York's Home Performance with Energy Star (HPwES) program.3 The GJGNY financing program is a valuable test of whether alternatives to credit scores can be used to responsibly expand credit opportunities for households that do not qualify for traditional lending products and, in doing so, enable more households to make energy efficiency upgrades.

  5. QER- Comment of Low-income Energy Affordability Network [MA

    Broader source: Energy.gov [DOE]

    Thank you, Secretary Moniz for the opportunity to submit testimony, I am entering this testimony to call attention to the Secretary and DOE staff, that DOE has operated a successful energy efficiency program for low income renters and home owners since DOE’s creation as a department, that leverages hundreds of millions of dollars in utility and other governmental and private investments...

  6. Family Moderate Income Homeowners In New York State

    Broader source: Energy.gov [DOE]

    "Family Moderate Income Homeowners In New York State: Enhancing Resource Accessibility Through Process Improvement and Targeted Outreach," by Residential Energy Efficiency Solutions, July 10, 2012, Arlington, Virginia. Provides an overview of broadening accessibility to financing through process improvement and targeted outreach.

  7. Average household expected to save $675 at the pump in 2015

    U.S. Energy Information Administration (EIA) Indexed Site

    Average household expected to save $675 at the pump in 2015 Although retail gasoline prices have risen in recent weeks U.S. consumers are still expected to save about $675 per household in motor fuel costs this year. In its new monthly forecast, the U.S. Energy Information Administration says the average pump price for regular grade gasoline in 2015 will be $2.43 per gallon. That's about 93 cents lower than last year's average. The savings for consumers will be even bigger during the

  8. EERE Success Story-Kingston Creek Hydro Project Powers 100 Households |

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Department of Energy Kingston Creek Hydro Project Powers 100 Households EERE Success Story-Kingston Creek Hydro Project Powers 100 Households August 21, 2013 - 12:00am Addthis Nevada-based contracting firm Nevada Controls, LLC used a low-interest loan from the Nevada State Office of Energy's Revolving Loan Fund to help construct a hydropower project in the small Nevada town of Kingston. The Kingston Creek Project-benefitting the Young Brothers Ranch-is a 175-kilowatt hydro generation plant

  9. Drivers of U.S. Household Energy Consumption, 1980-2009

    U.S. Energy Information Administration (EIA) Indexed Site

    Drivers of U.S. Household Energy Consumption, 1980-2009 February 2015 Independent Statistics & Analysis www.eia.gov U.S. Department of Energy Washington, DC 20585 U.S. Energy Information Administration | Drivers of U.S. Household Energy Consumption, 1980-2009 i This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data, analyses, and forecasts are independent of approval by any

  10. Households to pay more than expected to stay warm this winter

    U.S. Energy Information Administration (EIA) Indexed Site

    Households to pay more than expected to stay warm this winter Following a colder-than-expected November, U.S. households are forecast to consume more heating fuels than previously expected....resulting in higher heating bills. Homeowners that rely on natural gas will see their total winter expenses rise nearly 13 percent from last winter....while users of electric heat will see a 2.6 percent increase in costs. That's the latest forecast from the U.S. Energy Information Administration. Propane

  11. Effects of federal income taxes on the cash flow, operating revenue, and net income of electric utilities

    SciTech Connect (OSTI)

    Moore, J.T.

    1982-01-01

    The idea to do this research was suggested by the efforts of some consumer groups and others to seek passage of a law in the United States to exempt investor-owned electric utilities from federal income taxes. The goal of the consumer groups is to reduce the charges to utility customers (which is measured in this study by the amount of the operating revenues of the utilities) while not causing any harm to the utilities. The population of interest consisted of all investor-owned electric utilities included on a current Compustat utility tape. In the analysis of the data, the changes in cash flow, operating revenue, and net income were summarized by the 89 utilities as a total group and by the division of the utilities into smaller groups or combinations which used the same accounting methods during the test period. The results of this research suggest the following conclusions concerning the change to a situation in which electric utilities are not subject to federal income taxes: (1) as a group, the decrease in cash flow would be significant, (2) as a group, the decrease in operating revenue (charges to customers) would not be significant, (3) as a group, the increase in net income would be significant, and (4) in analyzing the effects of any financial adjustments or changes on electric utilities, the accounting policies used to the utilities are an important factor.

  12. U.S. Department of Energy National Nuclear Security Administration

    Broader source: Energy.gov (indexed) [DOE]

    ... Low-income populations refer to households with incomes below the Federal poverty ... approximately 15% of the households had annual incomes below the Federal poverty level. ...

  13. Slide 1

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Need 3 Significant number of low-income customers. * 12% of families below federal poverty level. * 18% of households receive food stamps. * 34% have household incomes income...

  14. "Table HC15.3 Household Characteristics by Four Most Populated...

    U.S. Energy Information Administration (EIA) Indexed Site

    "Income Relative to Poverty Line" "Below 100 Percent",16.6,1.5,1,1.5,... " 1. Below 150 percent of poverty line or 60 percent of median State ...

  15. Oregon State Energy-Efficiency Appliance Rebate Program Helps Low-Income Families

    Broader source: Energy.gov [DOE]

    Statewide program provides low-income homeowners with rebates on money-saving, energy-efficient appliances.

  16. Low Income Consumer Utility Issues: A National Perspective

    SciTech Connect (OSTI)

    Eisenberg, J

    2001-03-26

    This report has been prepared to provide low-income advocates and other stakeholders information on the energy burden faced by low-income customers and programs designed to alleviate that burden in various states. The report describes programs designed to lower payments, manage arrearages, weatherize and provide other energy efficiency measures, educate consumers, increase outreach to the target It discusses the costs and benefits of the population, and evaluate the programs. various options--to the degree this information is available--and describes attempts to quantify benefits that have heretofore not been quantified. The purpose of this report is to enable the low-income advocates and others to assess the options and design program most suitable for the citizens of their states or jurisdictions. It is not the authors' intent to recommend a particular course of action but, based on our broad experience in the field, to provide the information necessary for others to do so. We would be happy to answer any questions or provide further documentation on any of the material presented herein. The original edition of this report was prepared for the Utah Committee on Consumer Services, pursuant to a contract with the National Consumer Law Center (NCLC), to provide information to the Utah Low-Income Task Force established by the Utah Public Service, Commission. Attachment 1 is drawn from NCLC's 1998 Supplement to its Access to Utility Services; NCLC plans to update this list in 2001, and it will be available then from NCLC. This report has been updated by the authors for this edition.

  17. Value-added agriculture offers small agribusinesses additional income

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    potential Value-added agriculture Community Connections: Your link to news and opportunities from Los Alamos National Laboratory Latest Issue: September 1, 2016 all issues All Issues » submit Value-added agriculture offers small agribusinesses additional income potential Closing the gap between raw product and end user September 1, 2015 Las Nueve Niñas Winery wine label. Las Nueve Niñas Winery wine label. Contact Community Programs Director Kathy Keith Email Editor Ute Haker Email Instead

  18. Household-level dynamics of food waste production and related beliefs, attitudes, and behaviours in Guelph, Ontario

    SciTech Connect (OSTI)

    Parizeau, Kate; Massow, Mike von; Martin, Ralph

    2015-01-15

    Highlights: • We combined household waste stream weights with survey data. • We examine relationships between waste and food-related practices and beliefs. • Families and large households produced more total waste, but less waste per capita. • Food awareness and waste awareness were related to reduced food waste. • Convenience lifestyles were differentially associated with food waste. - Abstract: It has been estimated that Canadians waste $27 billion of food annually, and that half of that waste occurs at the household level (Gooch et al., 2010). There are social, environmental, and economic implications for this scale of food waste, and source separation of organic waste is an increasingly common municipal intervention. There is relatively little research that assesses the dynamics of household food waste (particularly in Canada). The purpose of this study is to combine observations of organic, recyclable, and garbage waste production rates to survey results of food waste-related beliefs, attitudes, and behaviours at the household level in the mid-sized municipality of Guelph, Ontario. Waste weights and surveys were obtained from 68 households in the summer of 2013. The results of this study indicate multiple relationships between food waste production and household shopping practices, food preparation behaviours, household waste management practices, and food-related attitudes, beliefs, and lifestyles. Notably, we observed that food awareness, waste awareness, family lifestyles, and convenience lifestyles were related to food waste production. We conclude that it is important to understand the diversity of factors that can influence food wasting behaviours at the household level in order to design waste management systems and policies to reduce food waste.

  19. Table 2.6 Household End Uses: Fuel Types, Appliances, and Electronics, Selected Years, 1978-2009

    U.S. Energy Information Administration (EIA) Indexed Site

    6 Household End Uses: Fuel Types, Appliances, and Electronics, Selected Years, 1978-2009 Appliance Year Change 1978 1979 1980 1981 1982 1984 1987 1990 1993 1997 2001 2005 2009 1980 to 2009 Total Households (millions) 77 78 82 83 84 86 91 94 97 101 107 111 114 32 Percent of Households<//td> Space Heating - Main Fuel 1 Natural Gas 55 55 55 56 57 55 55 55 53 52 55 52 50 -5 Electricity 2 16 17 18 17 16 17 20 23 26 29 29 30 35 17 Liquefied Petroleum Gases 4 5 5 4 5 5 5 5 5 5 5 5 5 0 Distillate

  20. The importance of China's household sector for black carbon emissions - article no. L12708

    SciTech Connect (OSTI)

    Streets, D.G.; Aunan, K.

    2005-06-30

    The combustion of coal and biofuels in Chinese households is a large source of black carbon (BC), representing about 10-15% of total global emissions during the past two decades, depending on the year. How the Chinese household sector develops during the next 50 years will have an important bearing on future aerosol concentrations, because the range of possible outcomes (about 550 Gg yr{sup -1}) is greater than total BC emissions in either the United States or Europe (each about 400-500 Gg yr{sup -1}). In some Intergovernmental Panel on Climate Change scenarios biofuels persist in rural China for at least the next 50 years, whereas in other scenarios a transition to cleaner fuels and technologies effectively mitigates BC emissions. This paper discusses measures and policies that would help this transition and also raises the possibility of including BC emission reductions as a post-Kyoto option for China and other developing countries.

  1. Characterization of household hazardous waste from Marin County, California, and New Orleans, Louisiana

    SciTech Connect (OSTI)

    Rathje, W.L.; Wilson, D.C.; Lambou, V.W.; Herndon, R.C.

    1987-09-01

    There is a growing concern that certain constituents of common household products, that are discarded in residential garbage, may be potentially harmful to human health and the environment by adversely affecting the quality of ground and surface water. A survey of hazardous wastes in residential garbage from Marin County, California, and New Orleans, Louisiana, was conducted in order to determine the amount and characteristics of such wastes that are entering municipal landfills. The results of the survey indicate that approximately 642 metric tons of hazardous waste are discarded per year for the New Orleans study area and approximately 259 metric tons are discarded per year for the Marin County study area. Even though the percent of hazardous household waste in the garbage discarded in both study areas was less than 1%, it represents a significant quantity of hazardous waste because of the large volume of garbage involved.

  2. Buildings Energy Data Book: 2.9 Low-Income Housing

    Buildings Energy Data Book [EERE]

    0 2005 Average Energy Expenditures per Household Member and per Square Foot, by Weatherization Eligibility ($2010) Members/ Hhold Hhold Total U.S. Households 780 2.6 0.86 Federally Eligible 617 2.7 1.10 Federally Ineligible 844 2.5 0.82 Below 100% Poverty Line 603 2.7 1.14 Source(s): 1,442 EIA, 2005 Residential Energy Consumption Survey: Household Energy Consumption and Expenditures Tables, Oct. 2008, Table US1 part2; EIA, Annual Energy Review 2010, Oct. 2011, Appendix D, p. 353 for price

  3. Evaluating the income and employment impacts of gas cooling technologies

    SciTech Connect (OSTI)

    Hughes, P.J.; Laitner, S.

    1995-03-01

    The purpose of this study is to estimate the potential employment and income benefits of the emerging market for gas cooling products. The emphasis here is on exports because that is the major opportunity for the U.S. heating, ventilating, and air-conditioning (HVAC) industry. But domestic markets are also important and considered here because without a significant domestic market, it is unlikely that the plant investments, jobs, and income associated with gas cooling exports would be retained within the United States. The prospects for significant gas cooling exports appear promising for a variety of reasons. There is an expanding need for cooling in the developing world, natural gas is widely available, electric infrastructures are over-stressed in many areas, and the cost of building new gas infrastructure is modest compared to the cost of new electric infrastructure. Global gas cooling competition is currently limited, with Japanese and U.S. companies, and their foreign business partners, the only product sources. U.S. manufacturers of HVAC products are well positioned to compete globally, and are already one of the faster growing goods-exporting sectors of the U.S. economy. Net HVAC exports grew by over 800 percent from 1987 to 1992 and currently exceed $2.6 billion annually (ARI 1994). Net gas cooling job and income creation are estimated using an economic input-output model to compare a reference case to a gas cooling scenario. The reference case reflects current policies, practices, and trends with respect to conventional electric cooling technologies. The gas cooling scenario examines the impact of accelerated use of natural gas cooling technologies here and abroad.

  4. Identification of influencing municipal characteristics regarding household waste generation and their forecasting ability in Biscay

    SciTech Connect (OSTI)

    Oribe-Garcia, Iraia Kamara-Esteban, Oihane; Martin, Cristina; Macarulla-Arenaza, Ana M.; Alonso-Vicario, Ainhoa

    2015-05-15

    Highlights: • We have modelled household waste generation in Biscay municipalities. • We have identified relevant characteristics regarding household waste generation. • Factor models are used in order to identify the best subset of explicative variables. • Biscay’s municipalities are grouped by means of hierarchical clustering. - Abstract: The planning of waste management strategies needs tools to support decisions at all stages of the process. Accurate quantification of the waste to be generated is essential for both the daily management (short-term) and proper design of facilities (long-term). Designing without rigorous knowledge may have serious economic and environmental consequences. The present works aims at identifying relevant socio-economic features of municipalities regarding Household Waste (HW) generation by means of factor models. Factor models face two main drawbacks, data collection and identifying relevant explanatory variables within a heterogeneous group. Grouping similar characteristics observations within a group may favour the deduction of more robust models. The methodology followed has been tested with Biscay Province because it stands out for having very different municipalities ranging from very rural to urban ones. Two main models are developed, one for the overall province and a second one after clustering the municipalities. The results prove that relating municipalities with specific characteristics, improves the results in a very heterogeneous situation. The methodology has identified urban morphology, tourism activity, level of education and economic situation as the most influencing characteristics in HW generation.

  5. Evaluation of bulk paint worker exposure to solvents at household hazardous waste collection events

    SciTech Connect (OSTI)

    Cameron, M.

    1995-09-01

    In fiscal year 93/94, over 250 governmental agencies were involved in the collection of household hazardous wastes in the State of California. During that time, over 3,237,000 lbs. of oil based paint were collected in 9,640 drums. Most of this was in lab pack drums, which can only hold up to 20 one gallon cans. Cost for disposal of such drums is approximately $1000. In contrast, during the same year, 1,228,000 lbs. of flammable liquid were collected in 2,098 drums in bulk form. Incineration of bulked flammable liquids is approximately $135 per drum. Clearly, it is most cost effective to bulk flammable liquids at household hazardous waste events. Currently, this is the procedure used at most Temporary Household Hazardous Waste Collection Facilities (THHWCFs). THHWCFs are regulated by the Department of Toxic Substances Control (DTSC) under the new Permit-by Rule Regulations. These regulations specify certain requirements regarding traffic flow, emergency response notifications and prevention of exposure to the public. The regulations require that THHWCF operators bulk wastes only when the public is not present. [22 CCR, section 67450.4 (e) (2) (A)].Santa Clara County Environmental Health Department sponsors local THHWCF`s and does it`s own bulking. In order to save time and money, a variance from the regulation was requested and an employee monitoring program was initiated to determine actual exposure to workers. Results are presented.

  6. Simulation of gross and net erosion of high-Z materials in the DIII-D divertor

    SciTech Connect (OSTI)

    Wampler, William R.; Ding, R.; Stangeby, P. C.; Elder, J. D.; Tskhakaya, D.; Kirschner, A.; Guo, H. Y.; Chan, V. S.; McLean, A. G.; Snyder, P. B.; Rudakov, D. L.

    2015-12-17

    The three-dimensional Monte Carlo code ERO has been used to simulate dedicated DIII-D experiments in which Mo and W samples with different sizes were exposed to controlled and well-diagnosed divertor plasma conditions to measure the gross and net erosion rates. Experimentally, the net erosion rate is significantly reduced due to the high local redeposition probability of eroded high-Z materials, which according to the modelling is mainly controlled by the electric field and plasma density within the Chodura sheath. Similar redeposition ratios were obtained from ERO modelling with three different sheath models for small angles between the magnetic field and the material surface, mainly because of their similar mean ionization lengths. The modelled redeposition ratios are close to the measured value. Decreasing the potential drop across the sheath can suppress both gross and net erosion because sputtering yield is decreased due to lower incident energy while the redeposition ratio is not reduced owing to the higher electron density in the Chodura sheath. Taking into account material mixing in the ERO surface model, the net erosion rate of high-Z materials is shown to be strongly dependent on the carbon impurity concentration in the background plasma; higher carbon concentration can suppress net erosion. As a result, the principal experimental results such as net erosion rate and profile and redeposition ratio are well reproduced by the ERO simulations.

  7. Simulation of gross and net erosion of high-Z materials in the DIII-D divertor

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Wampler, William R.; Ding, R.; Stangeby, P. C.; Elder, J. D.; Tskhakaya, D.; Kirschner, A.; Guo, H. Y.; Chan, V. S.; McLean, A. G.; Snyder, P. B.; et al

    2015-12-17

    The three-dimensional Monte Carlo code ERO has been used to simulate dedicated DIII-D experiments in which Mo and W samples with different sizes were exposed to controlled and well-diagnosed divertor plasma conditions to measure the gross and net erosion rates. Experimentally, the net erosion rate is significantly reduced due to the high local redeposition probability of eroded high-Z materials, which according to the modelling is mainly controlled by the electric field and plasma density within the Chodura sheath. Similar redeposition ratios were obtained from ERO modelling with three different sheath models for small angles between the magnetic field and themore » material surface, mainly because of their similar mean ionization lengths. The modelled redeposition ratios are close to the measured value. Decreasing the potential drop across the sheath can suppress both gross and net erosion because sputtering yield is decreased due to lower incident energy while the redeposition ratio is not reduced owing to the higher electron density in the Chodura sheath. Taking into account material mixing in the ERO surface model, the net erosion rate of high-Z materials is shown to be strongly dependent on the carbon impurity concentration in the background plasma; higher carbon concentration can suppress net erosion. As a result, the principal experimental results such as net erosion rate and profile and redeposition ratio are well reproduced by the ERO simulations.« less

  8. A structural analysis of natural gas consumption by income class from 1987 to 1993

    SciTech Connect (OSTI)

    Poyer, D.A.

    1996-12-01

    This study had two major objectives: (1) assess and compare changes in natural gas consumption between 1987 and 1993 by income group and (2) assess the potential influence of energy policy on observed changes in natural gas consumption over time and across income groups. This analysis used U.S. Department of Energy (DOE) data files and involved both the generation of simple descriptive statistics and the use of multivariate regression analysis. The consumption of natural gas by the groups was studied over a six-year period. The results showed that: (1) natural gas use was substantially higher for the highest income group than for the two lower income groups and (2) natural gas consumption declined for the lowest and middle income quintiles and increased for the highest income quintile between 1987 and 1990; between 1990 and 1993, consumption increased for the lowest and middle income quintile, but remained relatively constant for the highest income quintile. The relative importance of the structural and variable factors in explaining consumption changes between survey periods varies by income group. The analysis provides two major energy policy implications: (1) natural gas intensity has been the highest for the lowest income group, indicating that this group is more vulnerable to sudden changes in demand-indicator variables, in particular weather-related variables, than increase natural gas consumption, and (2) the fall in natural gas intensity between 1987 and 1993 may indicate that energy policy has had some impact on reducing natural gas consumption. 11 refs., 4 figs., 16 tabs.

  9. Household`s choices of efficiency levels for appliances: Using stated- and revealed-preference data to identify the importance of rebates and financing arrangements

    SciTech Connect (OSTI)

    Train, K.; Atherton, T.

    1994-11-01

    We examine customers` choice between standard and high-efficiency equipment, and the impact of utility incentives such as rebates and loans on this decision. Using data from interviews with 400 households, we identify the factors that customers consider in their choice of efficiency level for appliances and the relative importance of these factors. We build a model that describes customers` choices and can be used to predict choices in future situations under changes in the attributes of appliances and in the utility`s DSM and as part of the appliance-choice component of utilities` end-use forecasting systems. As examples, the model is used to predict the impacts of: doubling the size of rebates, replacing rebates with financing programs, and offering loans and rebates as alternative options for customers.

  10. Shared Renewable Energy for Low-to-Moderate Income Consumers: Policy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Guidelines and Model Provisions | Department of Energy Shared Renewable Energy for Low-to-Moderate Income Consumers: Policy Guidelines and Model Provisions Shared Renewable Energy for Low-to-Moderate Income Consumers: Policy Guidelines and Model Provisions The Shared Renewable Energy for Low-to Moderate-Income Consumers: Policy Guidelines and Model Provisions provides information and tools for policymakers, regulators, utilities, shared renewable energy developers, program administrators and

  11. Maldives-Program for Scaling Up Renewable Energy in Low Income...

    Open Energy Info (EERE)

    number of low income countries for energy efficiency, renewable energy and access to modern sustainable energy. The SREP stimulates economic growth through the scaled-up...

  12. Nepal-Program for Scaling Up Renewable Energy in Low Income Countries...

    Open Energy Info (EERE)

    number of low income countries for energy efficiency, renewable energy and access to modern sustainable energy. The SREP stimulates economic growth through the scaled-up...

  13. Honduras-Program for Scaling Up Renewable Energy in Low Income...

    Open Energy Info (EERE)

    number of low income countries for energy efficiency, renewable energy and access to modern sustainable energy. The SREP stimulates economic growth through the scaled-up...

  14. Kenya-Program for Scaling Up Renewable Energy in Low Income Countries...

    Open Energy Info (EERE)

    number of low income countries for energy efficiency, renewable energy and access to modern sustainable energy. The SREP stimulates economic growth through the scaled-up...

  15. Mali-Program for Scaling Up Renewable Energy in Low Income Countries...

    Open Energy Info (EERE)

    number of low income countries for energy efficiency, renewable energy and access to modern sustainable energy. The SREP stimulates economic growth through the scaled-up...

  16. Tailored Marketing for Low-income and Under-Represented Population Segments (201)

    Broader source: Energy.gov [DOE]

    Better Buildings Residential Network Peer Exchange Call Series: Tailored Marketing for Low-Income and Under-Represented Population Segments (201), call slides and discussion summary.

  17. California Solar Initiative- Low-Income Solar Water Heating Rebate Program

    Broader source: Energy.gov [DOE]

    The California Public Utilities Commission (CPUC) voted in October 2011 to create the California Solar Initiative (CSI) Thermal Low-Income program for single and multifamily residential properties....

  18. Table HC6.10 Home Appliances Usage Indicators by Number of Household Members, 2005

    U.S. Energy Information Administration (EIA) Indexed Site

    0 Home Appliances Usage Indicators by Number of Household Members, 2005 Total.............................................................................. 111.1 30.0 34.8 18.4 15.9 12.0 Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day........................................... 8.2 1.4 1.9 1.4 1.0 2.4 2 Times A Day........................................................ 24.6 4.3 7.6 4.3 4.8 3.7 Once a Day............................................................ 42.3 9.9

  19. Table HC6.11 Home Electronics Characteristics by Number of Household Members, 2005

    U.S. Energy Information Administration (EIA) Indexed Site

    1 Home Electronics Characteristics by Number of Household Members, 2005 Total...................................................................... 111.1 30.0 34.8 18.4 15.9 12.0 Personal Computers Do Not Use a Personal Computer ................... 35.5 16.3 9.4 4.0 2.7 3.2 Use a Personal Computer................................ 75.6 13.8 25.4 14.4 13.2 8.8 Number of Desktop PCs 1.................................................................. 50.3 11.9 17.4 8.5 7.3 5.2

  20. Table HC6.12 Home Electronics Usage Indicators by Number of Household Members, 2005

    U.S. Energy Information Administration (EIA) Indexed Site

    2 Home Electronics Usage Indicators by Number of Household Members, 2005 Total................................................................................ 111.1 30.0 34.8 18.4 15.9 12.0 Personal Computers Do Not Use a Personal Computer............................. 35.5 16.3 9.4 4.0 2.7 3.2 Use a Personal Computer.......................................... 75.6 13.8 25.4 14.4 13.2 8.8 Most-Used Personal Computer Type of PC Desk-top Model.....................................................